1776points · 6d ago

GPT-6 Sol and Luna

openai.com·by OfficialTurkey·6d ago

Discussion 855 comments

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simonw·5d ago

GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.

Here's GPT-6 Luna pelicans: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

And GPT-6 Sol: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

Scroll to the bottom for the GPT-6 Sol max one: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...

For comparison, here are the pelicans I got for GPT-6 Astra: https://tools.simonwillison.net/markdown-svg-renderer?url=ht... - I still like the Astra Max one best.

Here's a comparison grid showing all of the GPT-6 and GPT-5.6 pelicans at all effort levels: https://static.simonwillison.net/static/2026/gpt-6-and-5.6.h...

The grid is actually really interesting, because it shows that the 5.6 family default to brighter colors than the 6 family.

gizmodo59·5d ago

6-luna is at the pareto for most of the tasks! I dont know how they make money here but its insane value from a closed source model. I'd go further and say it makes no sense (privacy, sovereignty etc aside) to use many other models as its not only expensive but also many providers don't have that much GPUs to serve at a significant volume. https://openrouter.ai/rankings?view=month#top-models 5.6 luna is already the most used model this month.

sieve·5d ago

My OpenCode Go stats for the last 30d:

Cached Read: ~6,500M

Input: ~150M

Output: ~20M

Approx $40 worth of usage across DeepSeek V4 Flash + MuseSpark Contributor 1.3. And a bit of both the GLM models. This is covered in a $10 subscription.

If I were to use Luna's API pricing:

$0.02 x 6,500 = $130

$0.20 x 150 = $30

$1.20 x 20 = $24

So $184. And this is assuming smaller coding sessions (<272K) beyond which Luna pricing doubles.

Cost wise, these models are nice for small stuff. Translations etc. Any model that does not provide multiple Mtoks of cached reads per cent is not very useful to me for coding workflows.

nearbuy·5d ago

This isn't right. You're comparing cost per token, but DeepSeek V4 Flash uses more tokens. Artificial Analysis found GPT 6 Luna to be significantly cheaper than DeepSeek: https://artificialanalysis.ai/models/comparisons?compare=dee...

sieve·5d ago

I do not (generally) trust benchmarks. I only trust what a model does with MY code.

Forget DS. I asked MiMo 2.6 yesterday to explain ML/LLMs to me succinctly and the pointed it at Karpathy's micrograd code. It produced a C implementation called `xor_mlp`, a tiny model that learnt how `xor` worked. I then asked it to produce a model that can play tictactoe without losing (mostly). It did. It supervised the training process and produced a compiled version with multiple switches. The pi-dev session is still running, so here are actual stats

↑45k ↓35k R1.0M CH99.4% $0.019 4.2%/1.0M (auto) - (opencode-go) mimo-v2.6-flash • high

And here is Luna on the same workflow (I had to poke and prod a bit to get what I wanted):

↑141 ↓34k R1.0M W43k CH95.3% $0.072 4.2%/1.1M (auto) (opencode-go) gpt-5.6-luna • high

I expect similar results from DS41F/MS13. Closer to MiMo costs than Luna.

So the "significantly cheaper" thing may not really hold, more so when Luna has to actually read my codebase to do the stuff that I want rather than rely on world knowledge. The 8-10x cache read cost differential itself will kill the token budget.

nearbuy·5d ago

With GPT-6 Luna (which is what the parent comment was talking about), that would come to 3.2¢, assuming GPT-6 used the same number of tokens.

I don't think you can guess more precisely than an order of magnitude from trying each once on one task.

asaddhamani·5d ago

Don’t know if it’s still true but with Chinese models, using Western API providers is significantly more expensive and using Chinese providers they will train on your inputs without exception. That has kept me from using these ultra cheap endpoints.

dudisubekti·5d ago

Artificialanalysis benchmark is a combination of a several benchmarks which might or might not represent realistic coding:

"Artificial Analysis Intelligence Index combines performance across 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, and AA-LCR v1.1."

Not saying it doesnt have any value but it's probably irrelevant if you use these AIs for a specific use case. Like for example Humanity Last Exam tests general knowledge, which is not very useful for coding.

It's best to go to the specific coding benchmarks and compare there.

aucisson_masque·5d ago

There is too many money involved, benchmark can’t be trusted.

csomar·5d ago

Does it use less tokens or we just get no accounting of the thinking tokens in OpenAI/Claude models?

KoolKat23·5d ago

According my model,

My cost is (I use nous as provider)

DeepSeek v4-flash-0731 • Your cost: $0.56

DeepSeek v4.1-flash • Your cost: $1.22

GPT-6 Luna • Your cost: $4.22

My usage is heavy on the cache. Apparently v4.1 flash uses 1.75 times as many tokens so still cheaper.

gizmodo59·5d ago

It’s not direct token to token pricing and everyone misses it. The cost is how much tokens to complete something multiplied by token pricing. I can have a model at .0001 per million tokens but it’s so inefficient that it takes 10B tokens to complete a task means it’s expensive.

sieve·5d ago

I am not designing rockets. Most of my work is bog standard hobbyist stuff: compilers, vms, sandboxes, system tools of various kinds, SSGs, markup languages, plain text ledgers etc. Even Gemma/Qwen running locally can manage this.

Frankly, I have no idea what people do with Opus/Fable etc. I don't think anything I do needs something that charges $50/M for output tokens.

apatheticonion·5d ago

Can confirm. I have been using DeepSeek since forever and it's so good I was able to write a compiler and native desktop applications with it. I use it as a coding assistant in my IDE so the results end up at the same quality I would write by hand.

I recently started a job that only uses Claude models. Opus and Sonnet are so slow you have no choice but to do multiple tasks in parallel. You create a git worktree, set off an agent to do something, another worktree, set out an agent - then play video games for 20 minutes until they complete the task (poorly).

You can't really do "guide coding" like you can with DeepSeek-style flash models because Claude is too slow.

I think the idea with slow frontier models is to end up with "software factories", where you just write tickets and send them to a harness that delegates work to agents/subagents. Your job is to prompt and review (and eventually just prompt).

Mathematically and assuming token prices/efficiency remains constant, the collective US AI industry needs to increase token usage by 15x before 2030 (3.5 years from now) to satisfy investors. With companies already implementing token limits, the only place from here is for frontier models to replace staff entirely to expand budgets for tokens. The only way to do that is to demonstrate the efficacy of software factories and headless agentic workflows.

Objectively, I have set up a software factory and I do see the utility of it, though I did it with DeepSeek and prices are 1% that of frontier models - which doesn't bode well for investors looking for an eventual return.

Heck, my old M1 MBP 32gb running Qwen 3.6 35b a3b sipping 10w when generating tokens is good enough for a lot of my guide-coding work - it's just a bit slow so I use DeepSeek instead. When hardware prices come down, I honestly wouldn't see a need to subscribe to any service, I'd just grow my own tokens at home.

unsupp0rted·5d ago

It sounds like you’re still writing code by hand and reading and reviewing code.

For that any decent model from the past year will do.

If you want to forget how to write code and not read generated code, then you need a very good frontier model, ideally one from 6-12 months in the future.

MitziMoto·5d ago

These are also the orders of magnitude of our production agents for our business (NOT coding). Cache reads are so heavy compared to anything else that it's the only price point that really matters, regular input and output are negligible.

I need aggressive cache read pricing with full prompt_cache_key support to have a model be financially viable for our workload. Right now Meta Muse 1.3 Contributor is the only one that makes sense--but we are starting Evals on the new MiMo 2.6 class to see how it holds up.

sieve·5d ago

I have used MiMo 2.5 extensively. MuseSpark and DS4 Flash are MUCH smarter than that one. But MiMo follows instructions diligently. So it has been useful as the implementer of a spec designed by Claude/Kimi.

One good thing about MiMo that I experience on OpenCode is the provider seems to cache tokens for much longer than MS13/DS4F. I have seen cache being hit for close to an hour after the last request. The corresponding timing for MS13/DS4F is in the 1-5 min range.

I am trying out MiMo 2.6 Flash as well.

gleenn·5d ago

Last I heard, caches had like a 5 minute TTL... doesn't that mean if you get up and make a coffee (hand pour over of course), that you are back at full price?

jmalicki·5d ago

I wish that was more programmable.

You can pay for higher cache time, you can pay for NVMe KV cache for an hour that can just be reloaded, etc., at a lesser tier you can pay for the KV cache to be stored on a network store (I guess I'm unclear if that last tier would be cheaper than recomputation, not even 100% sure of the NVMe with direct GPU<->storage DMA) depending on your model settings.

MitziMoto·5d ago

You can override it to 24 hours:

https://dev.meta.ai/docs/prompt-caching#cache-retention

Even at 5 minutes, if you're doing 100 agent runs in those 5 minutes, and 1 of them bills at full input price, it still hardly matters.

WinstonSmith84·5d ago

Maybe your numbers are right, but that's not been my experience. My typical workflow is Astra coordinating with Luna Max (5.6 back then) as both implementer and reviewer and sometimes Astra review as well when I've some distrust with Luna .. A day, I've been trying to replace Luna Max by Deepseek v4.1 flash and I've been burning about $7 worth of tokens in Fireworks in a single day. More than what my 20x OpenAI sub costs me, including Astra usage. And that was when Luna 5.6 was less capable and more expensive than Luna 6.0.

sieve·5d ago

I have written about my experience. I have also mentioned the kind of code I write. It is not react/js/css heavy stuff that I see a lot of people write. So the code bases are typically in the 5-50KLOC range. Freestanding C, Python, or maybe some TypeScript. And fairly modular. I can thus run models on specific modules without having them read everything into context.

So the workflows I mention work for this kind of stuff.

handfuloflight·5d ago

How long can OpenCode bleed for?

sieve·5d ago

Are they bleeding? Their multipliers seem to be reasonable. They are not offering $60 worth of usage for $10 on every model, only some. In the case of the expensive ones, it is only $15.

Given how subscription models work (not every one uses every last $ of their plan), they should achieve breakeven soon enough I guess.

ronsor·5d ago

They already stopped. That's why the service quality declined.

handfuloflight·5d ago

What did you notice?

infecto·5d ago

How can you compare a subscription which is most likely being subsidized with consumption pricing?

sieve·5d ago

I gave you the $40 option. Which is what it would cost if you used APIs on OpenRouter or elsewhere. Still beats Luna by 4-4.5x

infecto·5d ago

Ok great. I still don’t see how subscription costs can be compared to API.

ascorbic·5d ago

You can't compare a subscription to API prices. OpenCode Go is massively subsidised. Unlike the closed labs, we can say that for sure because we can see what they're paying for their tokens.

dcl·5d ago

How have you found Muse Spark 1.3? It doesn't get much mention, despite pretty good benchmarks. I've been using a bit at home and find it quite good, often finding mistakes made by Opus 5.

sieve·5d ago

MS13 is pretty sharp and has been my workhorse for the past month. It follows my coding style and commit/clean workflows referenced in AGENTS.md perfectly but has the habit of doing things without conferring with me (the Gemini problem). So you need some kind of instruction for that.

It starts failing around the 5-600K context mark, but you can have it generate a handover document and continue in the next session.

I would not use it at sticker price, but the Contributor version is priced just about right.

slopinthebag·5d ago

shocking. the code it generated, while technically working, was entirely garbage. i used it for code review and it flagged twenty issues, sol checked the review and found 75% of them were hallucinations. sol was much closer to reality. i no longer trust benchmarks at all because of it.

dcl·3d ago

Interesting. I have been asking it to review code from Opus 5 and it found tonnes of issues, Opus agreed with the findings too.

booty·5d ago

    I dont know how they make money here

Well, here's the neat thing: they don't!

Snark aside, Luna 5.6 was (is) an incredible game-changer.

adventured·5d ago

Luna is about suppressing inexpensive Chinese model competition.

It's super simple.

Gigantic hyper margin ad network = artificial subsidization of cost for various tiers = put the boot on the neck of Chinese competitors. There's no scenario where they can compete with what advertising margins make possible in terms of artificially lowering prices charged.

locknitpicker·5d ago

> Luna is about suppressing inexpensive Chinese model competition.

I think so too. To me the so-called Chinese local models are a clear move to prevent US companies to establish a foothold and build a moat around their business. US companies are clearly invested in a strategy to make themselves relevant with claims of major impressive achievements with the so called frontier models, and how these and only these are unblocking whole ranges of applications. At the same time, they are heavily invested in pushing AI on all absurd types of mundane tasks, such as transcribing meetings and... talking to your own kids?

In the meantime it's rather obvious that, in spite of all the propaganda, frontier models are required only in ultra niche applications, whereas the ability to run any model at all already provides most of the value. In fact, US companies have been renownee by dumbing down older generation models in what seems to be a desperate attempt to make newer models look better and influence their uptake rate.

So there is no better way to take the wind out of the US AI companies' sail than pulling a two-punch attack consisting of not inly releasing capable models that refute the "only US frontier will do the job" thesis but also releasing them for free to commodities them and eliminate the business impact of dumbing down models.

idbnstra·5d ago

> and... talking to your own kids?

i don't doubt they're pushing for using AI for that, but i'm curious of examples of where they're doing this. commercials, ads, etc.

supernovae·3d ago

Everyone keeps saying this, but I don't believe it's true. I think Luna is just an MLA or sparse architecture like all the flash variants and it's just cheap to run.

In any case, over the past few years, the only thing that has gotten more expensive is the hardware to run local models while API and Subs have gotten more affordable or feature rich while remaining same price.

They can compete because they have the compute to run the volume and if it's good on agentic work, people will be less incentivised to use other models for "Tasky-y" work.

It's literally increasing their market opportunity

mordae·5d ago

Chinese buy their tokens at home. West as a market is an afterthought for their companies them. Western AI is banned, so only used via resellers by small fish, not companies. US has zero presence at that huge market, and absolutely not a moat.

They are buying Huawei accelerators in bulk to serve their local customers. The whole system is currently optimized to deliver a lot of cheap LLMs and hardware for them to run on.

larodi·5d ago

> Well, here's the neat thing: they don't!

perhaps it then does mean - squeeze as much as you can get off this actual free usage.

atoav·5d ago

"We lose money on ever sale, but we plan to make it up in volume"

Barbing·5d ago

*govt bailouts

adventured·5d ago

They're closing in a billion users. That's Google search territory.

OpenAI is sitting on a $100+ billion ad network, incoming.

They're not going to need a government bailout, they're going to be a spigot of cash production.

Every single thread on HN keeps saying the same ridiculous thing, going on a year now. It's like they've never heard of advertising, which SV specializes in. It's like they're oblivious to the fact that every mega platform with so many users becomes an ad goldmine, and GPT's context positioning is even richer than search.

krat0sprakhar·5d ago

Can't agree more. Between 5.6 Luna and Gemini 3.8 flash I'm so happy for the value I'm getting for my dollar (subscription pricing not API pricing) :)

jadbox·5d ago

Gemini 3.8 Flash looks like its better than v7 Luna/Sol on DeepSWE v1.1 while at $0.75 per million input tokens and $3.75 per million output tokens. Luna is much cheaper, but Flash has nearly Astra's performance for under the price of Sol ($2/$10).

antupis·5d ago

Flash thinks much more so it’s pretty much line with Sol for performance. That said I like flash coding style much more than OpenAi models.

jeffnash·5d ago

out of curiosity, what type of code/language do you usually use flash to write?

krat0sprakhar·5d ago

TBH: I really like how fast 3.8 Flash is... Once I have clear plan, I feel quite confident in delegating large parts of implementation to Flash and Luna

mgkimsal·5d ago

Maddening for a bit - I've got problems that Flash is better on, and some Luna is better on, but I generally don't know until one has wasted time/tokens. Then I switch to the other one and... it's often just... bam - done. Correctly. I can't find the patterns ahead of time to determine what model I should be using first. :/ That said, I've been alternating between both the last month or so and they've both been pretty good compared to earlier models.

Citizen_Lame·5d ago

Gemini 3.8 Flash and 3.1 Pro are pure rubbish. Very little thinking, mediocre and usually incorrect results. They cannot be compared to frontier models.

anukin·5d ago

This is my experience as well. I am surprised that lot of people find it much better than Luna.

oh_no·5d ago

look at token use, 3.8 flash is a huge token hog compared to openai models

user43928·5d ago

6-luna is no improvement over 5.6, merely a price cut.

And info from the help page with message limits suggests the 50% price cut does not apply to the subscription, where they applied only a 1/3 price cut instead.

I'm not thrilled with this release.

Opus 5.5, which matches GPT-6 Astra performance at a cheaper price, is much more interesting.

InsideOutSanta·5d ago

> I dont know how they make money here

By raising it from investors.

GolfPopper·5d ago

To whom they promise the Sun, the Moon, and the Stars. Roflmao. Whatever the merits of the underlying technology, the business model is pure hucksterism.

the__alchemist·5d ago

How does 6-Luna xhigh compare to 6-Sol medium? Or more broadly newer/bigger model with lower effort vs older/smaller higher effort?

knicholes·5d ago

Read the link! It's in there.

7777777phil·5d ago

I guess I have to update my pareto front then: https://philippdubach.com/posts/jev-model-router-for-pi/

zozbot234·5d ago

MiMo 2.6 Pro is at the Pareto frontier (the one where you only need 20% of the smarts for 80% of the tasks) according to Artificial Analysis, nicely filling in as a substitute for a hypothetical 'GPT-6 Terra' (which doesn't exist as far as we know). That's pretty darn impressive from an open model.

Ternari·5d ago

That's not what the Pareto frontier is; you're mixing up Pareto frontier with Pareto principle.

https://en.wikipedia.org/wiki/Pareto_front

https://en.wikipedia.org/wiki/Pareto_principle

Rexxar·5d ago

Despite the error in the parenthesis, it's exactly what he says: https://artificialanalysis.ai/?intelligence-category=text-on...

Ternari·5d ago

I was just responding to the error in the parenthesis.

supernovae·3d ago

mimo 2.6 is kinda dumb and over tuned though but not bad for a checkpoint testing their RL

matznerd·5d ago

Simon, love your work, one piece of minor feedback for the individual model pages is to make the font of the model name potentially bigger than (and above) the conversation id (which means nothing to the audience) "2026-09-22T18:28:00 conversation: 01m355zvyw8946qyraa8zpz6h9 id: 01m355zvyx47zxx5c6q6b3fg0m#".

I had all the tabs open individually and harder to scan which model is which... otherwise keep up the great work! I like the grid view a lot. (Also the pages have no OG images set, which impacts what the link looks like shared)...

simonw·5d ago

That's a good idea. It's the default output for my `llm logs` command, but that header could at least show the model ID.

OG images will require me to move away from publishing in a Gist and linking to from a JavaScript page that loads the Gist. Probably worthwhile though.

matznerd·5d ago

I think you can make it work without leaving Gists by using a Cloudflare Worker as a workaround. The Worker sits in front of the renderer page and adds the og tags to the HTML before it's sent out. You'd also need to turn the SVGs in the Gist into a PNG for the og:image, and decide if you want a grid or just one image, any text formatting, and how long to cache...

I got it working in a quick local test (grid of all the reasoning efforts, cached per Gist, loads from the raw Gist URL so it doesn't hit the GitHub API rate limit).

Code + prompt + notes here: https://gist.github.com/matznerd/ece297107bd99ac028c7962c217...

Basic concept is to:

1. Put a Worker on the /markdown-svg-renderer route. Normal visitors get your page exactly as it is now.

2. When a link has ?url=<gist>, the Worker reads the Gist and adds og:title, og:description and og:image to the page's HTML. Link previewers like Slack and iMessage don't run JS, so this is the only way they see them.

3. og:image points to a second Worker URL (og.png?url=<gist>). It takes the SVGs from the Gist, puts them in a grid, and converts it to a PNG, since previewers won't show SVGs.

4. Both results get cached per Gist, so each Gist is only fetched and rendered once, even with a lot of traffic.

Things to customize:

- Title and description (mine: "gpt-6-luna SVG of a pelican riding a bicycle" / "6 runs, reasoning effort none to max")

- Grid of all runs vs just one image, plus layout, labels and font

- How long to cache (I used a day, but edited Gists keep the old preview until it expires)

Cu3PO42·5d ago

I find it very interesting that for both these models we such a clear progression of better images with higher thinking levels from 'hardly useful' to 'pretty nice'. I feel on many other models low and max are much closer.

saretup·5d ago

Not that this benchmark is super relevant anymore but these look worse than I expected.

simonw·5d ago

Yeah, it's interesting how much worse they are than the Astra pelicans. I think that reflects a tiny bit of genuine value still left in the benchmark, to be honest.

hdz·5d ago

Tons of value left, especially for open source models. I would say the benchmark is yet to be truly saturated (just look at the legs and seat to see what I am talking about) and I always look forward to seeing them. Thank you!

Kotlopou·5d ago

To me the main upshot of this benchmark is precisely that the pelicans still usually look a bit wonky. It's bizarre, since this definitely has a good solution, but it's in line with my experience that memorization of the training set just... isn't happening very much? As in, whether a model fails or not doesn't have much to do with whether that exact question was likely posed many times before.

nomel·5d ago

I think some additional value would be had by seeing how well it can modify the pelican.

Like, "now facing left", "sitting on the handlebars", or "with green spokes" to see if it can break out of some pretty obvious statistics in the training data!

And, there's always asking for an STL rather than an SVG!

alansaber·5d ago

It would be extremely funny if the explosion in SVG generation capability in particular was a result of this benchmark

gtirloni·5d ago

What's the relevance of the pelican benchmark when models probably saw it during training? Didn't OpenAI stop testing against SWE-Something because it was tainted?

simonw·5d ago

If they train for the benchmark, how come many of the pelicans produced by their different models at different reasoning levels still suck?

That aside, the relevance these days is in comparing models and effort levels within the same model families - hence the comparison grids.

genidoi·5d ago

It's not a benchmark, it is a meme benchmark.

a3w·5d ago

Memes are arguably the web scale of benchmarks.

ljm·5d ago

AI reproducing Xtranormal video clips like NodeJS Is Web Scale should be the new benchmark.

If the dialogue is slop and not like the old memes then it fails.

mkotlikov·5d ago

How come the pelicans get older with more reasoning? Is GPT 6 taunting us with our mortality?

zahlman·5d ago

Probably it's easier to convey youth than age with a lower level of detail.

dom96·5d ago

It's surprising but MiMo V2.6 Pro performs better and is cheaper than GPT 6 Sol on my benchmark[1]. Open weight models are really snapping at the heels of the major western models.

1 - https://bench.killswitch-lang.org

dmazin·5d ago

> GPT-6 Luna being half the price of GPT-5.6 Luna is a really big deal.

Is it? It was already too cheap to meter for me. Luna 6 is actually worse on some benchmarks than 5.6. I’d have loved improved performance for 2x the price than ~equal performance for 0.5x the price.

agentcoops·5d ago

I’ve been doing really heavy text analysis work with LLMs where false negatives/misses are important to minimize and my god did I hit cost thresholds quickly with 5.6 Luna — it was the first time I felt motivated to seriously work with local open models, even if inference was degraded for the task. Cheaper and much better inference now brings me back to the closed models for better or worse.

FusionX·5d ago

5.6 Luna was already discounted at half the price on OpenRouter. Looks like they made it permanent.

onlyrealcuzzo·5d ago

Hopefully Terra 6 slots somewhat nicely into this space.

user43928·5d ago

Yes, I am mildly disappointed with these releases.

I expected a Fable 5 -> Opus 5 situation, where GPT 6 Sol would perform on par with GPT 6 Astra.

Instead it's more like a price cut on GPT 5.6 Sol, and I'll have to stick with Astra for my work.

The only thing I can hope for is that more users switching to the GPT 6 Sol model frees capacity, allowing OpenAI to hand out some usage resets.

zigzag312·5d ago

Yeah me too. Maybe that place will occupy the Astra Minor model that appeared in Microsoft's Azure model config. As Sol and Sonnet are now similarly priced (unless Sonnet 5.5 will reduce its price).

user43928·5d ago

Good point!

Maybe they are keeping the cheaper Astra alternative back for their Dev Day next week Tuesday.

m_fayer·6d ago

I've been working with agents all year, but 5.6 Sol was some sort of sweet spot for me. Something about how it communicated verbally and its engineering instincts just clicked for me, and I was able to somehow predict it and jam with it. Like a colleague you click with. It's the first model I've gotten attached to. I'm concerned that whatever model supercedes it, while technically better, just won't feel quite as natural to work with. And this makes me feel very professionally vulnerable to the labs. I miss the days when my crucial tooling came from companies as reliable and predictable as, say, Jetbrains.

NorthSouthNorth·6d ago

Completely agree. I've been using 5.6 still even with Astra available to me for most tasks. It's funny how much of this is just "vibes" because I cannot quantify what it is. Astra is definitely better when I have an ambitious feature, but in like 9/10 tasks I prefer working with 5.6 Sol. A few weeks ago when the limits were seemingly higher, having 5.6 on fast mode was a good time.

bryanhogan·5d ago

I have also been using 5.6 Sol instead of 6. I found 6 to burn through my usage incredibly quick, making it somewhat unusable because I wouldn't be able to get anything done.

My results with 5.6 Sol were quite similar to 6, although I haven't tested it that much.

fnordpiglet·5d ago

I have issues with astra having a full task list in front of it and doing an Opus 5 move and announcing it’s about to begin then end the turn and wait. Typically I can get it to work one step at a time then stop. It’s maddening. 5.6 was a workhorse.

jauntywundrkind·5d ago

Astra is 100% conpletionist no chill alien.

It wants things beyond what the mortals (us) know to reach for. It's not good at explaining itself, it doesn't show it's thinking. It's often not wrong. But the no compromises attitude can be unbearable to deal with. Especially given how little it cares about telling us.

dannyw·5d ago

If you’re using the API, both OpenAI and Anthropic models will happily update you on what it’s doing in significant and frequent detail with system prompting. You’re not getting raw/hidden thinking, but what you’re describing is more behavioural quirks of the harness and its system prompts.

The other explanation is just as part of ‘token efficiency’

throwuxiytayq·5d ago

You can override the system prompt in Codex, but AGENTS.md should probably work as well. Ask the agent to communicate intermediary updates more often using the “commentary” channel.

jauntywundrkind·5d ago

thanks for the advice. i'll dig into this more.

that could help tackle half of the problems here. i do think the other 100% completionist part is something i'm more used to steering through with llm usage, have negotiated fora while, and that Astra is particularly an astronaut whose instincts are extremely strongly in the direction of foreseeing and outdesigning potential problems, that it is rarely going to pick a practical sensible clear path on it's own.

capital_guy·5d ago

I tend to agree. it's by far the best coding model i've ever worked with, including astra and if i remember correctly fable, and it's unbelievably smooth at just getting the work done and communicating in simple terms.

if GPT 6 Sol is just 5.6 at half the price it will be everything i really ever wanted.

manojlds·5d ago

Does the price really matter when you are on subscription? Are we getting more usage or are we getting same usage and the cost for openai is lower?

joseda-hg·5d ago

So far, yes

They usually reduce usage consumption in line with cost reductions (But not always 1:1)

makeavish·5d ago

Don’t think in zero sum terms. OpenAI can’t burn money infinitely, efficient models are better for everyone

apitman·5d ago

Similar for me. gpt-5.6-sol high has been my go-to for months. One of the reasons I'm pushing myself to try open models more is because it lends some level of guarantee I can continue to use the same tool as long as I want to. And I think we may just be getting to the point the open models are >= 5.6 Sol for coding.

redox99·6d ago

Same. In fact I found 6 Astra to be a downgrade in situations where I didn't need the extra intelligence.

cmrdporcupine·6d ago

Yeah.

Astra was/is superior for planning type tasks. It was capable of doing seemingly magic things with rather vague/lazy instructions ("I need to be able to test this on Windows, maybe a qemu VM or something? Shrug." ... 1 hour later "yeah i built you a whole qemu + eval windows image + harness of powershell scripts + shell scripts to retrieve & verify harness.").

And for UI work -- which is not something I do a lot of but do here and there -- it was clearly superior to 5.6 Sol.

But it also feels sloppier? Somehow. And too expensive to use.

We'll see how Sol 6 is.

jeffnash·5d ago

I felt this way with Sol in the 5.6 series and was one of the seemingly few people on this earth who liked Terra for that reason. I would often have a very specific code-manipulation ask, e.g. "add a parameter to this method, ensure all callers pass it in, if there is not a logical way to derive the parameter to be passed in a particular instance, flag this in your final response", and Sol would go on some rabbit hole side quest to refactor my codebase to determine some way to derive it rather than flagging it as I had asked.

Terra had the "workhorse" quality where it could do these changes in bulk and follow directions without being too 'smart' (but sloppy) as you described. Luna was a bit too dumb and would make sloppy mistakes; I see that more as a "run these tests and format the results" sort of model. Maybe 6 Luna will be better.

I also just reread your comment and realized the naming convention is still extremely confusing with respect to ordering of [Family]x[Model]x[Number].

m_fayer·5d ago

I also get good mileage out of Terra when I need a diligent workhorse. That's a good way to describe it. We should start using character archetypes when we describe models, it'll do more good than the dubious numbers and cherry-picked quotes. Maybe RPG character-type cliches? Myers Briggs?

jeffnash·5d ago

I fear the opposite will happen. Guy driving like a maniac almost side-swipes you in traffic? "Look at this 1-bit quantized Qwen 2.5 7B over here".

mavsman·5d ago

Glad you pointed out the UI work. I've been doing a lot of it and it's so much better than 5.6 as UI, it's unbelievable. I give it super ambiguous instructions and it's reading my mind. I do the same thing with 5.6 and I'm correcting it for a few minutes.

cmrdporcupine·5d ago

Update:

Sol 6 is a heaping pile of garbage. Just epic levels of slop. And r/codex etc is full of people noticing the same.

I've switched back to 5.6 Sol. What they're selling as Sol 6 is really what would have been Terra before, and it's awful.

Rapzid·5d ago

Yeah, I use Astra for destroying vaguely scoped asks and tasks, and then for high-level design and plan generations..

Otherwise I'm using 5.6 Sol for actual plan execution and review..

amluto·5d ago

I use Astra for rapidly consuming my token limit on a task that would not consume it on 5.6 Sol.

(I have not done anything quantitative here. For one thing, OpenAI’s billing pages and the codex-rs frontend make it pathetically difficult to get any real data. Some day I should wire up a proxy to extract actual stats.)

danabramov·5d ago

Same. The way I would describe it is that I can mostly leave 5.6 Sol overnight and trust that it makes good progress, maybe stumbling a bit and needing some correction for the remaining 20%.

If I leave Astra overnight, I'll wake up with three new different projects, each of them 20% done and having nothing to do with my original goal.

jijijijij·5d ago

The A in Astra stands for ADHD. It's featuring a neurodiversal net.

m_fayer·5d ago

I didn't think we'd get neurodivergent models until at least 2028.

bradly·6d ago

Not only was 6 worse the 5.6 Sol for my me, but it went through my Plus usage in minutes, while I could cruise for hours with 5.6. It would churn on a basic prompt for minutes and then just give up on usage limits.

Highlight and lowlight of my week was successfully convincing the OpenAI support chat robot to give me a refund for the month for my issues with 6 chewing threw my usage with no output.

jmuguy·5d ago

Yeah 5.6 Sol is what got me to switch from Anthropic. I couldn't deal with Claude's Ted Talk responses to literally everything. Sol has been nice and concise and just stays out of the way.

mcast·6d ago

It's a shame the labs don't open source their models after deprecating them. I get why, but, it's a piece of internet history I hope is preserved.

jeffnash·6d ago

At this point, the deciding factors for me between Claude Code 20x and Codex Pro 20x are:

1/ Usage limits: downstream of input/output cost, but resets and obscure windows and odd 20x plan / 5x plan != 4x usage math throw a wrench into it. Winner right now is Codex by a mile, especially when you factor in the fact that ChatGPT usage (even 6 Astra Pro) is essentially unmetered on the 20x plan. Always a bummer when asking if I should see a doctor about a rash means I can't code as much. It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems, giving better planning results or deeper code analysis without burning usage.

2/ Context window in the harness. Claude Code wins on this. There used to be a toml file workaround for Codex to extend the GPT context window to 1m, but this stopped working on the plans and only on per-token billing (ETA: noname120 pointed out this is no longer the case and it can be enabled again [1]). 252k is just not enough. Codex's compaction is very good, fwiw, but it happens so frequently that even a model as powerful as Astra sometimes loses the plot on long-running tasks.

3/ Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.

I've subscription hopped a bunch, and at times I've had both, but I keep coming back to Codex because it wins on 2/3.

ETA: apparently I haven't been Keeping Up With the Altmans and new 20x signups have been disabled for a few weeks. I am grandfathered in, which makes the comparison above pretty much moot.

[1]https://news.ycombinator.com/item?id=49806060

glub·5d ago

> Usage limits [...] Winner right now is Codex by a mile

This hasn't been the case since around July. If you measure usage in raw api costs, Anthropic is actually giving more on $200 than OpenAI now. This includes resets. Usage allocation difference would be humiliating for codex subs were it not for resets. But fixing usage limits with resets is ugly, and they're not good for your mental well-being.

> Context window in the harness

Codex now allows 1M for subs with config params. But generally speaking, you shouldn't really be using 1M context. If you accidentally send a request with say, ~700k context already accumulated in a session which is outside cache TTL, you're paying full cost of these 700k tokens.

> I've subscription hopped a bunch

OpenAI actually has a new strategy to prevent subscription hopping after their 2-3 month-long marketing push to get claude-folks to switch over:

you can't buy a $200 sub anymore. So if you cancel, you won't be able to get back in. Hostage situation, essentially.

EDIT: re: usage limits, oh-my-pi maintainer has been tracking this - https://nitter.xitter.cc/_can1357/status/2090075496948060372

rudedogg·5d ago

I’ve been a Claude user, switched to Codex expecting usage limits to be more loose but I can’t even get through a basic sysadmin task on the $20 plan using Sol medium before I hit the 5hr one.

I think I’m gonna move back to a Claude plan. I could barely hit the $200 limit if I went non-stop on programming tasks.

glub·5d ago

I think OpenAI essentially executed a bait-and-switch here, and they've lost a lot of goodwill with me, like Anthropic did, before them.

When they started the aggressive campaign, entire X (including myself, sadly) was full of posts about how "unlimited" codex usage is even on a $20 plan. Sam Altman was posting something in line of "we love our users, unlike Anthropic". Got my network to get codex subs because of the value compared to claude.

Then they gradually reduced the limits to the point where even $200 plan only lasts you just 1-2 days and $20 is basically unusable, then the hostage thing.

malshe·5d ago

I remember Tibo Sottiaux telling people on X how OI doesn't believe in 5 hour limit just a day or two before OI adopted it.

phyrex·5d ago

tbf that's only for the pro plan, not the two max plans

Numerlor·5d ago

I think the models getting dumber impacted that too, after a couple weeks both sol and Luna felt notably worse to me than they did at release

slopinthebag·5d ago

> Then they gradually reduced the limits to the point where even $200 plan only lasts you just 1-2 days

what? im on the $100 plan and ive literally never run out of usage, and thats mostly running Astra high.

maybe its the harness

qlte·5d ago

I do the bulk of work on Sol Medium/Low and don't have that experience on the $20 plan. If you said Astra I'd agree it's easy to burn through the 5 hours even on the lower reasoning levels.

Do you have /fast enabled by any chance?

rudedogg·5d ago

I don’t think so, I’ve seen it suggest I try it. I’ll double check when I get home though.

I was considering the $100 plan, but I hit the 5hr limit in an hour. So even with the $100 plan I figured I cant go non-stop on a single agent running Sol Medium

hirvi74·5d ago

Sorry if I am misunderstanding you, but I am pretty sure the $100 plan doesn’t have a 5hr usage limit. So, if that was what was preventing you from going non-stop, it might be worth it.

I am considering the plan myself. I just don’t know if I want to fork out $100 per month for something I will make $0 off of.

boardwaalk·5d ago

similar here: I tried Codex $20/mo on a trial and I ran out of 5hr usage mid way through a medium complexity task on a medium size model twice and gave up there. I don’t recall the equiv Claude plan being anything like that. Anecdata, but not great for OAI if they actually want to retain people on a trial.

cromka·5d ago

You don't get Fable on Claude 20 USD plan. You get Sol on equivalent Codex plan.

istjohn·5d ago

You meant Astra, not Sol, I think. But Opus 5.5 is slightly better than Fable and Astra now.

this_user·5d ago

Astra is barely usable even on the $100 plan. And that is if it doesn't just burn through 80% of your weekly quota in a couple of hours by continually expanding the scope of the task you gave it - while not noticing the failing tests that are right in front of it.

Opus is at least actually usable even on the small plan. The main downside is its insane writing style, but 5.5 seems to address that somewhat. Otherwise, you can just use your $20 OpenAI plan to have Luna de-slop Opus' prose, which seems to work fine.

Huppie·5d ago

I have a Claude Code hook that calls codex for a code review on commit time (Codex is set to Astra Medium) and it's been pretty good in general. It sometimes hits the 5hr limit but most of the time it provides really good feedback and because it's a completely different model it's mostly complementary to what Fable/Opus do themselves. IMHO it's been $20 well spent.

...but the few times I've tried to use codex for a moderately difficult task it burned through its limit extremely quickly.

joquarky·5d ago

On the $20 plan, you can't use Sol for much more than planning and review. Luna xhigh for the rest. Have Sol write the plan specifically for Luna so it adds more direction and validation to the plan.

hadlock·5d ago

I've run into hitting limits on the personal plan perhaps twice since the beginning of the year. But also I don't use the personal plan for coding tasks between 7am-noon M-F.

cromka·5d ago

But you don't get Fable on Claude 20 USD plan, then why compare it Sol on Codex 20 USD?

sisyphus15·5d ago

Sol is OpenAI's Opus, and Astra is OpenAI's Fable. Both pricing-wise, and performance-wise.

rudedogg·5d ago

Sol is their middle model. Luna is smallest. And Astra is big, their Fable equivalent.

matheusmoreira·5d ago

My code review benchmark put Sol 5.6 on the same performance tier as Fable 5.

https://www.matheusmoreira.com/articles/code-reviewing-lone-...

athrowaway3z·5d ago

I'm not sure the tokens can be compared like that between OpenAI/Anthropic.

When i swapped between a 200k Fable context into an Astra model (i was out of fable) the token usage in that context dropped to 150k or something.

Either there was a bug somewhere, or the same text got cut up very differently between providers.

glub·5d ago

That 50k was almost certainly accumulated encrypted reasoning tokens that would have been unreadable by astra.

athrowaway3z·5d ago

Ah that makes sense.

cameronh90·5d ago

To add my anecdote, while the Codex subscription appears to get you much fewer tokens as measured by cost, I find the amount of actual useful work that can be done by both subs to be about equal. Codex seems much less prone to burning millions of tokens just reading the codebase and doing nothing useful. That also makes it much quicker. Plus it actually does what I tell it with few mistakes first time, so less rework needed.

The Claude TUI is just so much better though so I'm hoping Opus 5.5 is actually good and not just benchmaxxed.

platinumrad·5d ago

Given that Anthropic models are very verbose and OpenAI models can be very concise, wouldn't a count of expected task completions be a better measurement than raw API costs?

glub·5d ago

Perhaps. But Sol/Astra also likes dumping pages of jargon-packed content at me, so I'm not sure it's that much different. I actually still prefer the way Fable talks to me, even considering the horrible claudisms.

But even if we leave that aside, OpenAI models are also much more eager than Anthropic, which are on the lazier side. Left unsupervised, Sol/Astra will attempt to build a sha256 verified rocket ship if you ask them to fix a race condition in your to-do list app. Anthropic models will do what you asked for, maybe even forget to implement parts of that ask, but they won't generally throw a slop granade at you.

I can leave Fable orchestrator unsupervised for ~2h. Leaving Sol/Astra unsupervised for ~2h means the next user turn will contain a message: "what are you doing and why?".

matheusmoreira·5d ago

Anthropic has a separate meter for Fable. I used to get like five Fable sessions per week and that's it.

OpenAI has no such nonsense. No separate meter. No five hour limits. I get to use Astra at max effort on literally every task if I want to, and even this somehow lasts me several days.

Anthropic got caught playing stupid "20x refers to the 5h limit" word games with their customers. Meanwhile, I have statistically verified that OpenAI Pro 20x = 4 * Pro 5x = 20 * Plus, exactly as advertised.

I quantified cybersecurity lockouts on my code review benchmark and they were significantly lower on OpenAI:

https://www.matheusmoreira.com/articles/code-reviewing-lone-...

My benchmark also suggests even OpenAI's Sol models can match Fable performance at a fraction of the cost.

OpenAI also used to have a ton of very nice features: unlimited chat separate from codex, allowing turns to finish even at 0% usage remaining. Sadly these got removed after abuse.

As a former Anthropic customer, OpenAI is simply the better company. There is no way around it. Good place to be while the chinese open weights models catch up. Claude is good but it doesn't make up for Anthropic's shenanigans.

ghostpepper·5d ago

OpenAI has 5 hour limits on the $20 plan. I agree about cybersecurity refusals though.

jrflo·5d ago

Do you have a source on the first note? I switched away from Claude around July because of how bad the usage limits were, and Codex gave me easily double the amount of usage per task completed. Would be interested to see if that's no longer the case.

glub·5d ago

Added link in edit. OMP maintainer has several claude and codex subs and he's been tracking usage since around July.

I haven't been tracking, but this roughly matches my experience with codex 20x and claude 20x subs. Claude subscription now lasts me 3-3.5 days on average. Codex is 2-2.5 days. This is work on same projects, with similarly sized tasks.

To make matters worse, I've merged a lot more code produced by fable than sol/astra.

InsideOutSanta·5d ago

I think the problem with Anthropic's plan is that Fable just destroys it. If you stick to Opus and below, the $200 plan goes from "using 50% of the weekly quota on the first day" to something much more reasonable.

albert_e·5d ago

> If you accidentally send a request with say, ~700k context already accumulated in a session which is outside cache TTL, you're paying full cost of these 700k tokens.

Thinking aloud:

The harness UI should probably implement a timer that shows whether you are still within Cache TTL since your last turn of the conversation.

elxr·5d ago

Also, OpenAI is just a company I'd rather support than Anthropic.

While you're understandably not including the values of the $20 standard plans on both, I find the generosity of then token limits on ChatGPT plus vs Claude Pro (it's a huge difference) to be good representation of their respective attitudes towards the average user. You literally cannot use Claude pro to build real software, unless you're extremely frugal with your prompts and don't try anything even a little ambitious.

Also, Anthropic has zero models comparable to Luna.

InsideOutSanta·5d ago

> Also, OpenAI is just a company I'd rather support than Anthropic.

They're both pretty horrible, but I find it difficult to find arguments for why Anthropic is worse than OpenAI, other than their doomtrolling. Which, in the grand scheme of things, doesn't even register.

Edit: forgot about the SpaceX thing.

andriy_koval·5d ago

> why Anthropic is worse than OpenAI

Anthropic is trying to kill open models way harder

nullc·5d ago

OpenAI just wants to make money, perhaps through underhanded tactics if they can get away with it.

Anthropic does all that but they're also populated by many people who believe they are building God and that they must build their god first in their own image so that it can take control of humanity and protect us from any competing god which is not built in their image. Their position is inherently paternalistic and authoritarian, and they consider suppression of competition not just important to the bottom line but to life in the universe. Under the doomer ethos there is no evil too great to rationalize.

There are plenty of wrongs done in the name of profit, but capitalists have nothing on zealots in terms of causing serious harm. Profit motives can be directed by influencing incentives, but zealotry is frequently terminal.

That isn't to say that there isn't some overlap-- the cultists have infected both organizations. But OpenAI has pretty consistently only given lip service to AI doom to the extent that it improves the bottom line, while (mis)Anthropic was founded specifically because OpenAI wasn't mentally ill enough.

elxr·5d ago

Well said. The superiority complexes from the Anthropic messaging on their presentations/blogs/articles is just too much, even for a frontier AI company.

Anthropic has great products, but it's not meaningfully better to 99% of devs that I'd rather support the company that doesn't constantly act in opposition to optimism and to the vibe I'd prefer for a 100 billion dollar (or however ridiculous amount they're worth now) tech company embraces.

AI doomerism is a genuine waste of time if you aren't actively pushing towards a better AI industry for everyone, not just the groups in full ideological alignment to your personal leanings.

elxr·5d ago

OpenAI has been way more open with users using their subscription plans on 3rd party tools.

That alone is reason enough. Also, I don't think either of them are horrible. That's honestly a ridiculous take considering how much people in here love their models, and how much they've advanced the industry forward.

jsw97·5d ago

For me the first point, openness to 3rd party, is the decider. I don’t want to build tooling around a completely closed model. I liked being able to use pi, and now I exclusively use my own harness which I modify the way I want. Not possible with Anthropic subscription.

elxr·5d ago

100% agree.

I often have the urge to design my own harness too (once I have more time). But even with the current mainstream harnesses out there, there's just to many hurdles if you wanted to mainly stick with anthropic models and need the subsidized pricing (from a sub).

ychnd·5d ago

They are both killing people / aiming for murder bots, aren't they?

ketzu·5d ago

> aiming for murder bots

Anthropic prohibits the use of claude models for development of lethal technology afaik eg [1].

[1] https://www.epc.eu/publication/the-pentagon-blacklisted-anth...

InsideOutSanta·5d ago

> Also, I don't think either of them are horrible. That's honestly a ridiculous take considering how much people in here love their models

That's a non-sequitur.

"Nestle is a great company, considering how much people love their chocolate."

elxr·5d ago

How about you tell me what makes the horrible then. There's pluses and minuses to both obviously, almost everyone around me have positive experiences with the product. They've innovated at a pace unheard of before 2026, and for openAI specifically the amount of value they've provided to me and family members (who aren't even developers in the slightest) has far outweighed the supposed horrible actions they've done.

Yeah I don't think the handling of copyrighted training data was correct, but I can't pretend I know what the correct solution to that issue is.

Speaking of OpenAI specifically, they don't price gouge people, they aren't aggressively anti-competitive, they're not nearly the perpetual hypocrisy machine that Anthropic is (which is one thing I actually really dislike).

Regarding Nestle, it's pretty obvious that the sentiment towards them is a lot more negative and they aren't universally loved by any group of people. Processed foods are by and large garbage nobody needs. Their use of forced labor is denounced by just about everyone. What have OpenAI/Anthropic done that's even similar in scope to the forced labor / modern slavery that people hate Nestle for.

If you had a company that genuinely helped hundreds of millions of people worldwide become more productive and more satisfied with their tools, and the overall sentiment towards your products within the industry is positive, then what argument would there be that your company is "horrible"? At least give some decent counter arguments.

ketzu·5d ago

> You literally cannot use Claude pro to build real software

Interestingly I would have drawn the exact opposite conclusion looking at my Claude and codex usage.

I can't get anything sustained out of codex in chatgpt plus, while I have been using Claude pro extensively and put on a lot of experimental task and features.

I ran into codex exhausting a 5h window on code review in minutes (like 3minutes) multiple times, while I could get Claude to implement 2~3 medium sized features with the same usage consumption.

(I also really dislike the usage resets in codex, they always make me feel like I use them wrong because I often just want to reset the 5h window, but they can only do both at once...)

therein·5d ago

They are both companies I'd rather not support. Not that our support for them has any material impact. NVIDIA is bankrolling them directly and indirectly.

bix6·5d ago

Reasons for this?

> Also, OpenAI is just a company I'd rather support than Anthropic.

elxr·5d ago

Their responses towards using their subscriptions on opencode for one. Second, Dario just has a habit of making completely doomer comments on the future of software engieering as a job and towards the open-weights model ecosystem.

Sure, he's free to say whatever especially considering the amount of revenue he's creating, but it's just an altitude that I prefer not to see.

usef-·5d ago

I think if they truly believe it's happening we generally want to encourage them to be honest with the public, though, don't we? We've spent decades complaining about ceos not being honest in the public risks that they see

killingtime74·5d ago

Last week he said they should pause research and today there just released newer and better models. His talk is completely meaningless.

hbrn·5d ago

I think opencode subscription issue is just a different marketing strategy. Neither company wants it, but OpenAI believes it's worth it as a marketing expense in the long run.

And Dario's "AI will kill us all" is the same as Sam's "AI will discover ALL science and we'll be building Dyson spheres".

Different flavors of the same BS.

platinumrad·5d ago

The first one terrifies people who really don't need to be. It's deeply unethical.

bix6·5d ago

And Sam is better?

CuriouslyC·5d ago

Sam is sketchier on a personal level, but judged just on the words coming out of their mouths, he's also much less paternalistic/controlling and more customer focused.

elxr·5d ago

Significantly.

felixgallo·5d ago

You'd rather literally support <i>Sam Altman>/i>? I mean, that's a position to take, for sure, but apparently several people still use Grok, so maybe it's not all that surprising.

"You literally cannot use Claude pro to build real software, unless you're extremely frugal with your prompts and don't try anything even a little ambitious" - that's way past ridiculous. Even just using Fable most of the time, working on several ambitious projects, I have a hard time hitting the limit with a Max plan.

qwerpy·5d ago

Lol Grok users catching strays here. I enjoy it and it has built some nice things for me as a hobbyist. The attitude of the company is more just quietly build cool things rather than Anthropic's holier-than-thou condescending attitude coupled with the over the top self-serving doomerism.

noname120·6d ago

> It's also is a godsend if you use an MCP like oracle to automate the process of calling the Pro model on particularly tough problems

As far as I know Codex (at least the GUI) can automatically call the ChatGPT Chat models (including Astra 6 Pro), you just need to @ a ChatGPT Chat conversation from within Codex and tell it when to use it.

> There used to be a toml file workaround for Codex to extend the GPT context window to 1m, but this stopped working on the plans and only on per-token billing

Not true, it works again[1]. I confirm that it works both on 5.6 Sol and Astra 6, possibly other models too.

[1] https://x.com/thsottiaux/status/2089082893804896524

jeffnash·5d ago

I actually haven't played with the GUI. I probably should now that the Linux version is in beta. My situation is kind of the reverse: I like using oracle to basically zip up my repo, ask GPT Pro to propose some sort of design or refactor based on the code, then provide a step by step implementation plan for a cheaper model to implement directly in a harness on my machine. It often takes upwards of 90 minutes to come up with something but I've never been disappointed by the results. I suppose I could do this and then save a step by referencing the oracle-created thread with the @ you mentioned

And re: the toml workaround, AWESOME! I appreciate you pointing these two things out, this is my highest-ROI HN comment thus far.

hintymad·5d ago

> Ability to use the plan outside of the official harness. Codex wins. Anthropic does shit like bills requests as extra usage if it sees a hermes.md in a commit.

I'm quite puzzled about why Anthropic is so hellbent on blocking other coding agents. It's not like Claude Code has any secret sauce, right? And doesn't Anthropic make monkey off API usage, and their magic is on the model side anyway?

glub·5d ago

It's for lock-in - same reason why it took them so long to finally support AGENTS.md.

But to be fair, they don't really enforce the harness rule that much anymore. I guess if your harness doesn't do a lot of weird things like a lot of cache misses, or triggers some distillation attacks, or some broader Chinese fingerprints, they're tongue-in-cheek okay with you using a third party harness.

codybontecou·5d ago

You can use Claude’s subscription in Pi now? Last I tried it opted for extra usage.

glub·5d ago

Not natively, as it's still a ToS violation and adding that in pi would go against pi principles, but there are many plugins/proxies that make it work.

oh-my-pi supports it natively (again, still a ToS violation), by impersonating claude code's fingerprints.

I have been using oh-my-pi with 3 claude subs for the past few months without any issues. Even native server-side OAI/ANT compaction works out of the box.

goosejuice·5d ago

It's pretty unclear because they have two somewhat competing sets of documentation but I believe using the agent sdk with a harness like pi is not against the ToS if it's for yourself.

omp is definitely against ToS though

https://support.claude.com/en/articles/15036540-use-the-clau...

> Unless previously approved, Anthropic does not allow third party developers to offer claude.ai login or rate limits for their products, including agents built on the Claude Agent SDK.

manx·5d ago

Yes, you need an extension that uses the claude code credentials from the file system, like this: https://github.com/fdietze/pi-claude-auth

Works pretty well for me, even with latest opus-5-5

spacebanana7·5d ago

This feels like a horrible precedent. Billing based on data like commits feels like it opens the door to tech stack based billing in general - could we see different prices for people who use other devtools Anthropic doesn't like? Makes me feel grateful for open models

InsideOutSanta·5d ago

They want to lock people into using the Claude Code ecosystem to make switching to other providers more difficult.

nl·5d ago

Originally it was because Anthropic was so compute constrained they relied on the extra care the Claude harness took with caching (heavy use of cache breakpoints etc) that other harnesses didn't.

I think that is less of a factor now, and I think Anthropic have backed off some on being as strict (eg, AFAIK they never implemented the two-tier "claude -p" pricing model they were planning)

saralily·3d ago

Meridian and DirectSDK work well to use a Claude MAX subscription in alternative harnesses.

sodacanner·6d ago

In my personal experience I currently get a lot, lot more usage on the 5x Claude plan than the 5x Codex plan.

Having limitless webUI ChatGPT usage is much better user experience, though. I'll give them that.

(edit: Sol-6 is half the price, so maybe the usage limits are going to be way better.)

basisword·5d ago

I've been using Claude Pro and recently gave Codex a try again. Both on the $20 plans. I get so much more usage with Claude. It's night and day for me. Codex runs out constantly, whereas Claude I hit limits very rarely.

DaSHacka·5d ago

Same here, especially as I stick with Opus 4.6. My usage limits truly feel limitless, I can just hammer a task over and over again until completion.

Meanwhile I just burned ~20% of my weekly quota with Astra making one config file for a service.

rbranson·5d ago

Assuming you are doing coding, I'm curious how would you characterize tne majority of your work (language, domain, frontend/backend, etc)?

basisword·5d ago

iOS development mostly. I'm using the Pro plans as it's work on personal projects outside my day job and I'm able to get just enough usage from those plans to get me through each day.

jeffnash·5d ago

I'm actually interested to see how the token discount maps to the usage limit consumption. The conspiracy theorist in me wonders if they're making up the discount and resultant load increase on the API end by reducing effective usage on the subscription end.

paulmist·5d ago

> Winner right now is Codex by a mile

Opposite in my experience. I need to limit codex to 500k on medium/low, still run out in 2-3 days with 1 CLI window. CC gives me 4-5 medium/high days with 2-3 CLI windows, and Opus is still great for other regular dumb engineering/refactoring.

On the other hand my head starts to hurt if I read Opus for too long, hopefully they fixed it with 5.5.

joshstrange·5d ago

This is my experience. After months of hearing how Codex limits were way higher I bumped to the $100/mo plan after hitting my limits a day early on Claude due to some heavy usage + Fable (not normal for me, I often fit nicely in the $200/mo plan). I hit the usage limit in a day with a single agent running on codex and the tiny context window was stifling. Yes, I'm comparing a $100 to a $200 plan but I extrapolated the usage (4x'd it) and it still wasn't close, I got way more done with Opus.

Using Agentsview (which might have it's own issues) I was getting ~$200 of API usage in my 1 week Codex window (paid $100) vs ~$5,000 of API usage in 1 week for Claude (paid $200).

joshstrange·5d ago

Maybe it's due to 20x / 5x != 4 but I have the $200/mo Claude and $100/mo Codex and I get _way_ less usage on Codex, well under 1/4th the usage. In 1-2 days of semi-heavy _single_ agent usage with Sol High I can burn through my whole week of Codex. Again, this is not running multiple agents, just 1 at a time.

Compare that to Claude and I can run multiple agents on Opus almost indefinitely. YMMV of course but I was shocked at how quickly I burned through Codex usage.

On the context window, I feel so cramped on Codex, compacting happening every time I turn around is annoying. I didn't realize how much I enjoyed the Claude context window size.

rgbrenner·5d ago

Same experience. Have both subs. It's just not true anymore that Codex gives you more usage than Claude.

Makes me think they picked Codex, stopped trying Claude, and just hang on to outdated beliefs about the value they're receiving.

hirvi74·5d ago

Isn’t that to be expected when comparing one 20x plan to another 5x plan?

I am curious how the 5x plans differ between both providers.

malshe·5d ago

I have 5x on both of them. I get way more use from CC than Codex. Actually as we speak, I exhausted my Codex limit twice in the last two days. I am living on banked resets right now.

chrisweekly·5d ago

> "Codex's compaction is very good, fwiw, but it happens so frequently that..."

I appreciate and follow Matt Pocock's advice: avoid autocompaction. Compaction is lossy, which is ok when you're managing it at phase boundaries, but autocompact is lossy at the most inopportune times, firing mid-task and leading to agents going off the rails.

erichocean·5d ago

Bad advice, compaction is why Codex is so fantastic.

My conversations compact hundreds of times. By the time it has done a dozen or so compactions, it fully understands the work I want it to do (and how). It's almost like having a fine-tuned Astra model.

10/10, would recommend.

chrisweekly·5d ago

I'm not sure I follow; how is autocompaction (lossy summarization), applied at random times (vs strategically, between workflow phases), helpful to ensuring clarity of intent? Maybe you're saying that just plowing ahead and living with the signal loss along the way works well enough for your purposes. In which case, ok, YMMV, different strokes.... but paying attention to context quality and being deliberate about when to compact vs handoff vs delegate to subagents is most definitely not "bad advice".

edg5000·5d ago

I agree with @erichocean on this. In theory, compaction is bad. But in practice I found the model is smart enough to write critical details down somewhere, and post-compaction the model doesn't make assumptions. A small amount of time is lost reading materials, but the benefit is that you can operate unbounded vs doing small controlled chunks, which is what I used to do with Opus back in the day. Now I just give it as big a task as I can think of.

elcritch·5d ago

This approach got good with Sol. With 5.5 I'd break tasks up, record planning docs, etc.

Now with Sol I rarely bother. It's really good at remembering the salient details. Its also great at continuing a pattern I setup, like commit after finishing each feature block, etc.

slopinthebag·5d ago

not my experience at all. compaction during a task is fatal since you lose all of the details of edits and progress halfway through. compacting after task completion is fine though.

leokennis·5d ago

From the perspective of “an average person”, ChatGPT is delivering fantastic products.

- For general chat and web search, occasional image editing, small coding work, document review etc. ChatGPT Plus is basically limitless and “just works” since 5.6. I’ve yet to give it some task it cannot do.

- When given sensible instructions, it hardly annoys with weird phrasing, glazing, or annoying constructs.

- The apps are very good (ignoring the initially terrible Codex app)

It’s easily my best spent $23 a month.

jeremyjh·5d ago

You can get a lot of Codex usage out of that same sub on top of ChatGPT usage. Its a really good value and you can use that sub in any harness. In OMP I have Sol high as the orchestrator, Sol max as Planner & Reviewer, Luna max as task/coder. Very good setup. I'm on pro now and there are weekends when I use half a week's usage but I'll have 5 or 6 sessions going at once for many hours each day.

lionkor·5d ago

I find that subagents usually burn more tokens and take longer, and produce about the same quality. A real killer use-case is using a VERY cheap subagent to do a lot of work, or reviews. Don't be fooled into thinking that a "scout" subagent will gather enough info for a "coder" agent to just start working.

jeremyjh·4d ago

OMP also does a lot of rewinds - where the orchestrator comes up with findings on its own and rolls back to a previous turn with a summary update. I don't know if it always chooses correctly between rewinds and sub-agents, but it seems to do a pretty good job. Luna is SO MUCH cheaper that even if it spends 30K overhead in context its still much less costly, and when they work in parallel its faster too.

sergiotapia·5d ago

This is quite interesting, I wasn't aware omp has a way to set up different models for planner/orchestrator/task.

ssk42·5d ago

/model then roles and also /agents for when a model chooses to delegate out sub agents

sergiotapia·5d ago

Thank you so much

shepherdjerred·5d ago

What is OMP?

vinzenzu·5d ago

oh my pi https://omp.sh/

PestoDiRucola·5d ago

Not even for the average person. Luna is an amazing model for most coding tasks.

maxnevermind·5d ago

> From the perspective of “an average person”, ChatGPT is delivering fantastic products.

It is a honeymoon still, enshittification is coming, who knows how that will look like given how much more expensive to run LLMs backed user experience. Some back of the envelope calculations: 300 million US users * 20$ a month * 12 months = 72 billion $ a year. 72B$ is some spare change for AI labs. That assuming entire US will be subs which is unlikely and outside of the US there are not many rich countries consuming it, India is the next market, then Brazil and Philippines I think, not super rich counties to say the least. I believe total revenue to just pay for the capex build out by the end 2027 should be on the scale of hundreds of billions a year.

mikeg8·5d ago

Analysis totally excludes enterprise customer demand and or paid API usage which will only increase as apps integrate this into future knowledge work workflows.

maxnevermind·5d ago

Indeed, that is where the money is. Though enterprise is more focused on efficiently than retail and I'm not sure if they won't drift away from frontier models.

brokencode·5d ago

Depends on whether the frontier models can keep on offering better performance. The real efficiency is getting work done faster and better.

Compared to a $100k salary, a few hundred dollars a month is insignificant. If you can make the employee even just a few percent more efficient, it’s worth it.

maxnevermind·5d ago

> If you can make the employee even just a few percent more efficient, it’s worth it.

Are/were you in a position to make such decisions or it is a guess? I'm not but given certain evidence I doubt that few percent will cut it. I know some of the richest companies on the planet from SF Bay Area who won't give lunch for free to their engineers. So I'm not sure about "few percent" :-D 10x we were promised, now that is more interesting but we all know that 10x engineers is nonsense.

phoghed·5d ago

On the other hand enterprises are gearing up to pay for shit like $99/user Agent 365, or paying for huge PTU reservations that go almost completely unused on weekends and holidays.

jr3592·5d ago

> ignoring the initially terrible Codex app

Still needs a LOT of work IMO.

arnaudsm·5d ago

The current bugginess of Codex is the proof that OpenAI hasn't "achieved AGI internally" yet.

lukevp·5d ago

Why is that? Humans are considered AGI and we make godawful software 90% of the time.

XCSme·5d ago

I use a lot of ChatGPT remotez and 70% of the times is unusable and buggy (prompts disappear, a lot of errors, buttons don't work, etc.)

pookieinc·6d ago

I don't see how anyone can be using Claude with prices like this, it's pretty incredible what the OpenAI team is doing, w.r.t model quality and pricing.

  Prices per 1M tokens     Claude Opus 5.5    Claude Opus 5
   Cache reads              $0.20              $0.50
   Input tokens             $4                 $5
   Output tokens            $20                $25
   Cache writes             $5                 $6.25

Model

Input

Output

Price reduction

GPT‑6 Sol vs. GPT‑5.6 Sol

$4 → $2

$20 → $10

50% cheaper

GPT‑6 Luna vs. GPT‑5.6 Luna

$0.20 → $0.10

$1.20 → $0.50

50% cheaper

hombre_fatal·6d ago

I mainly use Codex/Sol to review my plans drafted by Fable. But beyond that, Astra blows through usage limits too fast to be a daily driver and writes weird code despite what my "house style" is, and Codex is behind Claude Code in terms of critical features like seeing what's going on in subagents.

The parent + subagent workflow has become critical for keeping the reasoning agent (parent) context-lean while also letting me chat to the main agent while work is getting done.

My main process is to use Fable to reason and then spawn Opus subagents, and I get amazing results, and I'm always looking into what the subagents are doing.

jorl17·5d ago

Astra is:

- Unbearably slow

- A token eating machine like no other

- Constantly compacting

- A model (like other GPT ones) that hides thinking traces and thinking summaries, which infuriates me

I've been in the Claude camp for a while, but the way it writes has left me with a a brick for a brain and wanted to see if Astra was as good as they say. Well, I can't know, because in the time it takes for it to actually build anything useful, I've moved to other ideas.

Unbearably, annoyingly slow. I keep thinking I must be doing something wrong.

user43928·5d ago

It also feels slow for me and compacts often.

However, it is not a 'token eating machine'. In fact it uses a third of the output tokens of Opus 5.5, Fable 5.1, or Opus 5.

17k for Astra xhigh vs 61-66k.

jorl17·5d ago

You're right, it's probably quite unfair of me to say it eats lots of tokens when I am paying double for claude than codex and complaining about tokens.

The rest still stands, though.

But if I've learned anything is that in a 2 months I might have completely turned around, who knows

thatguymike·5d ago

Have you tweaked the reasoning level? “High” can mean different things across different models.

jorl17·5d ago

The thing is that this thing is constantly compacting.... I get 1M context with Claude and ~256k with Astra. Even if the compaction loses much less information on OAI's side, it takes so long it's barely any use for me...

I've tried High and Max. They have produced decent results, but they're so slow.... I will try to lower it a bit and see the difference, but it's a delicate balance: I don't want to waste literal hours on the incorrect reasoning level to only then have to spend those hours and tokens to do it right.

At this very moment, Astra has been working for 1h15m on a task. At this rate I genuinely expect it to take about 10 hours. I feel like claude would do it in at least a third of that. Let's see if the quality justifies the slowness (it better)

hoangnnguyen·5d ago

If you want a mix between both codex/claude code/pi for leveraging different models and harnesses, you can give ai-devkit agent orchestration a try

mfiguiere·6d ago

Also, batch processing prices are still 50% off, which put GPT-6 Sol and GPT-6 Luna at $5 and $0.25 for output.

https://developers.openai.com/api/docs/pricing?latest-pricin...

joshstrange·6d ago

As someone who has used Claude Code and Codex the prices don't matter in the same way but I found that I burned through my usage way faster on Codex even though I regularly hear that the Codex plans go further. That was not my experience and the intelligence was comparable to what I was getting in Claude.

If these price changes mean that coding plans have effectively more usage then that's great, but Codex is surviving on resets from my own experience using it. I was glad to go back to Claude.

etothet·6d ago

For API usage, sure. But plenty of people have subscriptions where these differences effectively don’t matter.

esafak·5d ago

It should matter; if their costs go down you'll get more usage.

etothet·5d ago

Just because a provider is charging less, doesn't mean their cost went down. This is probably especially true with the big players that are trying to stay competitive.

mchusma·6d ago

Opus 5.5 is incredible so far, its going to get used. Fable is much better than Astra for me in practice, and Sol is not marketed as better.

Its a great release, I will use both heavily.

rgbrenner·5d ago

The major difference being the 1M token context window. Once you exceed 272K input tokens, Codex Sol is roughly the same price as Opus; and Astra similar to Fable.

shmoil·6d ago

>> GPT‑6 Sol vs. GPT‑5.6 Sol

>> $4 → $2

>> $20 → $10

Do you mean 100% more expensive? GPT 6 is 100% more expensive than 5.6 per your post.

blovescoffee·6d ago

It's before and after following the arrow. 6 is the cheaper one.

s3p·5d ago

then it should be GPT 5.6 Sol vs. GPT 6 Sol

jameshart·5d ago

This is how the price cut is portrayed on OpenAI’s site. They are trying to say the prices have moved from the higher ones to the lower ones.

yzydserd·6d ago

Yes very poor proofreading!

onlyrealcuzzo·6d ago

I could already run Sol High on 3 concurrent side projects 24/7 and not run out of quota.

This is great, but practically, I'm not going to start working on more side projects.

Perhaps in another 6-12 months I'll be fine to drop down to $20/m instead of $200.

charliegoforit·6d ago

How much does it cost you per month to have that much sol high usage and what do you use, api? Through what? Thank you

onlyrealcuzzo·6d ago

$200/mo

A lot of what I'm doing has pretty expensive build/testing processes between iterations - even on a 40 core machine - so I'm not burning tokens 24/7 like some people may.

I'd guess I'm probably spending >50% of the time running tests & build processes & tooling and the remainder is purely burning tokens.

I also have some internal tooling (that I will hopefully open source soon) that makes LLMs substantially more correct (thus more efficient) - so there's that, too.

wyre·6d ago

they said quota so i would imagine the $200 subscription. Probably through Codex or Pi coding agents.

adam_arthur·5d ago

You can now start to add automations on top of typical dev flows.

There are a ton of use cases that open up with cheaper models.

E.g. extensive security scanning on every PR, quality scans, adversarial reviews etc

onlyrealcuzzo·5d ago

I already do all that, and a lot more...

Someone1234·6d ago

Have they solved GPT5.6 SOL's propensity to over-engineer and over-complicate? You'd ask SOL to do something relatively simple, and find four single-use methods, an interface, and a factory-factory.

I actually preferred 5.6-Terra not because it is technically superior (it isn't) but because it had better instincts to NOT do this stuff.

PS - Speaking of better instincts, have they closed the UI-design gap at all? I keep a Claude subscription just because /design produces significantly higher quality UI design/UI feedback/UI refinement than anything I've seen from OpenAI.

cmrdporcupine·6d ago

Astra 6 was a huge improvement over Sol 5.6 for UI work. I haven't tried Sol 6 yet for it (it's only been a few minutes).

The GPT / Codex models have always been "overengineer" personalities. I prefer that to "I left a pile of race conditions lying around and big gaps in testing" though, which is what I was getting from Opus at times.

But yes both Astra and Sol veer on the side of paranoid. And honestly that's better for team work. For solo work where you just want to yeet something, it can be tiring.

You learn to tame the GPT "personality" on this front by combing over once a week and asking it to find and exterminate pointless tests, clean abstractions etc.

faitswulff·5d ago

The UI design gap is something I’ve noticed as well, in things as simple as ASCII diagrams. Claude has a more human touch. All the diagrams GPT 5.6 generated for me were dressed up lists with too many pipe symbols.

howunfortunate·5d ago

> design

I force OpenAI models to use image generation for design, then an iteration loop until it matches the image gen.

This is frustratingly manual and takes many more repetitions compared to Claude (and especially Claude Design) which "just work", but it's a big step change over the default.

kairosisme·5d ago

FWIW, Codex's "Product Design" plugin basically is this workflow (minus built-in iteration, but the model in one prompt will still do its own internal iteration), it'll generate 3 images for you to choose from and then build from that + feedback

MisterMunchkin·5d ago

Claude has a bunch of designs hardcoded into it, which is why all of the websites and presentations it makes look the same.

c0rruptbytes·5d ago

have you tried using lower efforts?

superfrank·5d ago

Not the person you're responding to, but I have the same feelings they do and to answer your question for me at least, yes.

IMO 5.6 Sol had this weird dead zone between medium and high where medium under engineered and took short cuts and high over engineered and ignored instructions it didn't agree under the guise of trying being helpful. The whole 5.6 line was the first release from OpenAI where it felt like reasoning level really mattered and was incredibly finicky.

I haven't felt similar issues with GPT 6 though and am very happy with Astra low/med/high as my default choices depending on the task.

In general, I felt like with 5.6 the effort level did less than previous to make the models smarter and more just increased the complexity of the response. I have a half joke theory based only on vibes that OpenAI splitting 5.6 into Sol/Terra/Luna is where the intelligence split happened and so the effort levels were just like "think harder about the decision you already made". So like if the model decided the earth was flat on low effort it'd just say something like "the earth is flat because the horizon is flat". If it was on xhigh reasoning it'd give you a massively complex answer about how the sun reflects light because of the ozone layer and why people flying in planes can see a curve. In both cases though, adding more effort wouldn't get it to realize the earth was round. It just made the answer about it being flat more complex.

To be clear, that theory is not meant to be taken too seriously. It's not based on anything other than vibes. It's just my way of explaining to myself something I'm frustrated about to myself.

mike_hearn·5d ago

Also try just using Luna. It's a very capable coding model and doesn't over-engineer.

superfrank·5d ago

I've tried 5.6 Luna many times. I don't think it's any better. I definitely use it from certain tasks, but I find it the most susceptible to that conspiracy theory example I gave above.

I didn't love any of the 5.6 models, but weirdly I think I liked Terra the best. I still wouldn't call it amazing though. I'm still very happy with my codex plan, but 5.6 just wasn't my cup of tea I guess.

Definitely giving 6 Luna and Sol a try this week though.

delillos·5d ago

Getting to the point where these headlines depress me. I just wish they would stop getting better. I don't know where my career is gonna be in a few years.

lurker616·5d ago

I don't get this sentiment. Think of the future innovations possible with faster research and computation - space exploration, DNA-based health improvements, robotic helpers - read a few sci-fi books to imagine what the future can be! Computer science doesn't have to end with everybody getting laid off due to no more CRUD apps needed.

timdiggerm·5d ago

It doesn't have to, sure, maybe, but what indication do you see that the owners of these companies have any future in mind other than one in which they are in control of the majority of the wealth and power? These are private companies, not publicly owned infrastructure.

genidoi·5d ago

Even if you don't agree with the sentiment it's not hard to understand. The pace of AI improvement has strictly accelerated, and strict acceleration is likely going to be the way things go from here. To many, this means mourning a steadier future that is no longer likely to happen.

desterothx·5d ago

i dont really see strict acceleration, in fact i would say weve kept up roughly the same velocity since the first reasoning models

agent_turtle·5d ago

if anything we've slowed down. i have no clue what the acceleration folks are talking about. we've been getting diminishing returns on models; the growth has been in usage and tools.

idbnstra·5d ago

yeah, while gpt-6 is impressive, is it really as impressive as people thought it would be back in the times of gpt 3.5 or 4? let alone "omg ai acceleration agi" levels of impressive?

wartywhoa23·5d ago

Selling points straight from AI PR department texbooks, try better.

jstummbillig·5d ago

Humans are terribly bad at empathy and ethics.

If you, like me, don't like the idea of your standard of living dropping to that of even just the mean human being on earth, I find it extremely painful to watch people justifying their way around not trying absolutely anything to raise everyone to at least our current level. Increasing productivity is demonstrably such a way, while many other experiments are so far just that: Experiments + wishful thinking.

If that merely means realigning/cutting current jobs (a process, that is ongoing from the start of human civilization itself, which brought us prosperity and why the fuck would it stop now) to me it's a moral obligation to deal with that at some other level.

There is tons to do here, certainly including how we will do redistribution better, and quickly, etc. Let's get to it.

wartywhoa23·5d ago

> Let's get to it

And do what exactly? Subscribe for corporate AI brain implants? How does that solve inequality?

Also, thinking that you can bring low standards of living up to be on par with high in the current political landscape is a bit like that early Soviet space era promise about blooming apple trees on Mars.

It is guaranteed that they can only become equal by lowering the high.

valegrete·3d ago

For simplicity's sake, say you live on a world with exactly one other person. Between you both, 100% of all resources are allocated, but the other person has 100x the resources you do. Please explain how you would achieve equality by raising your resource level to match the other guy's. Technology enabling exploiting of new resources is not really an answer to the question, since developing that technology requires use of current resources, which means 100x the technology is available to the other guy.

vatsachak·5d ago

These things still can't solve problems in the right way. The benchmarks prove that they can solve problems. But in practice they will make your codebase look like the output of some compilation process

unified101·5d ago

I'm afraid this is "cope".

There's hardly any work you can think of which can't be done faster / beter with ai assistance, when your role is of reviewing and directing. If you have an anti-example, would like to hear.

vatsachak·5d ago

I really wish that LLMs could generate good quality code without repeated instructing.

Here's where I think the issue is; they are trained to solve a problem. Not how, just whether or not they did.

Example: I asked Luna to use parser combinators to parse an Excel sheet that was represented as sparse triples (row, column, data). It imported the library and wrote spaghetti if-statement soup to get it to work. I asked Astra to fix it and it just refined the spaghetti slightly. I was able to browbeat Astra into actually using the library to complete the task. Was it faster than me doing it by hand? Probably. Was it more frustrating? Way more.

And every time I review vibe code it's always the same. Bespoke functions everywhere, no greater themes or ideas. No bigger picture. Your code can't support much if it has no central themes. You can probably one-shot a three js game to post on r/singularity for updoots. Not real code though.

I feel like the optimal way to use an LLM is to code until you feel like the rest of a problem is trivial and then you hand it off. And sometimes they still erase my code and add their own style lol

ismayilkarimli·5d ago

Not OP but here's my take on it.

> There's hardly any work you can think of which can't be done faster / beter with ai assistance

True, and someone needs to be the creative brain behind the decisions. AI can help you implement. When I say help, I mean literally help because one-shotting and vague prompts can get you only so far, usually with a lackluster result. While AI is good at analyzing solutions, and finding out holes in one's thinking, ultimately, it is some creative actor that needs to understand the bigger picture to evaluate trade-offs, understand scope creeps, and spot overengineered implementations. For now that actor is a human.

> If you have an anti-example, would like to hear.

In my personal experience, especially with greenfield projects, smarter models tend to overengineer the solutions. However, I haven't used Fable and Astra models, maybe they are better at creative tasks without overengineering.

ghosty141·5d ago

I think it depends on what you think your job is.

If your job is/you enjoy writing the code and solving technical challenges then yes this changes very heavily and AI will do this more efficiently than a human.

But if your job is designing systems and implementing solutions and coming up with good code along the way then I don't see AI getting anywhere close to making you obsolete in the foreseeable future.

I personally don't enjoy writing C++ but I really enjoy solving problems.

desterothx·5d ago

the trouble is if i have to review/direct the model, suddenly we go from a 10x increase in speed to a 1-3x increase in speed. sure it will be faster, but im still limited by my reviewing/directing speed, which is slower than usual because I didn't write the code

michelsedgh·5d ago

If you were alive right before industrialization, you probably would’ve been one of the people wishing that would stop too.

boelboel·5d ago

+-3 generations of British people lived in roughly the same and in many cases worse conditions (life expectancy dropped during the early industrial revolution, severely in cities). As an average person you would not have been wrong to be against it. It was only in the 1860s-1880s that conditions got better because of bargaining power of the labour class and goodwill of some rich people, two things unlikely to repeat if something like AGI really happens.

cheeze·5d ago

This is the thing I mention often.

"Am I arguing against the shuttle loom!?"

Then I realize that the shuttle loom led to the rise of unions because of unfair treatment in factories and realize that we have a _long_ way to go.

phoghed·5d ago

On the other hand, because of the general level of education and broad access to written history, we know about the unions and have the playbook.

jakeydus·5d ago

But so do the builders of the shuttle loom and the controllers of capital...

estearum·5d ago

Most people who were afraid of industrialization at that point were correct to be afraid of it. It destroyed livelihoods, threw people into slave-like conditions, enabled the most immense violence ever seen, etc. etc.

wartywhoa23·5d ago

And don't forget WWI and WWII enabled by industrialization.

spixy·5d ago

Industrialization took decade or even more, AI took just a few years. AI is a quite a shock for our economy.

delillos·5d ago

Is the implication that industrialization was a net positive for our species?

mikeg8·5d ago

Not OP but that seems to be the implication. Let’s hear your argument against industrialization being net positive?

oblio·4d ago

> Let’s hear your argument against industrialization being net positive?

The main argument is that it's too early too judge it and at this point basically NO industrial process is sustainable.

michelsedgh·5d ago

All I can say is: THANK YOU!!

darkstar999·5d ago

Take solace remembering that we are all in the same boat.

In 1840 ~70% of the population was in agriculture. That is now ~2%. Things change.

tasercake·5d ago

Is that a US-specific number? World Bank stats put the percentage of global population engaged in agriculture at ~26% in 2023

mike_hearn·5d ago

It's about right for any developed western country.

runeks·4d ago

Because we import the agricultural products we consume from other countries?

f33d5173·3d ago

No because mechanization has made farming require far fewer people than in times past. The US and many western countries export more than they import.

sthuck·5d ago

Expectations are a funny thing, a year ago I thought all software industry will cut at least 30% in a year. It's very far from happening. A big change is obviously coming but now I think I'm good enough to last at least the next 5 years, which suddenly feels like a long time if you see it coming.

The truth is despite these very impressive improvements, most impressive work done by agents require many iterations running in a loop, with tens of thousands of dollars in API pricing. And it's still far from being always reliable. Somewhere along the way hardware will get better, energy will be cheaper, the market will be flooded by chips. There a physical world issues that limit all of these for now, thank god. I think 5 years is a good number.

The real damage is that enterprise work became unbearable. Slop code with slop code review, and overly verbose emails with repetitive presentations. And on the other hand, I now enjoy "coding" for myself like I'm 16 again. All I want to do is sit at home and build apps for myself and family. I barely go to work

philipwhiuk·5d ago

> Expectations are a funny thing, a year ago I thought all software industry will cut at least 30% in a year.

People overestimate the change in the short term and underestimate the long term. Timelines are hard.

Also predicting the first victims is harder - I don't know many that thought pure mathematics would be high on the list.

altcognito·5d ago

I keep repeating this too.

The history of the self driving car is apt to repeat as well. I remember thinking "2015, 2018 maybe at the latest." But as 2015 (and 2018) came and went, expectations were tempered.

We will see shortened development cycles, and maybe even orders of magnitude shorter development cycles.

But hard problems remain hard (there are only so many chips, materials research and biology are difficult problems). Manufacturing remains a choke point.

I'm more concerned that the absolute worst persons on the planet are in charge of many of these technologies. If those that are in charge are more concerned about allocating resources and power in their favor, the more dismal the future of all humanity will be (including for those in charge, but they can't see that due to self-interest bias)

mattmaroon·5d ago

I think the change might be orders of magnitude more software being written rather than an order of magnitude fewer developers. There is a HUGE induced demand coming when software is so cheap to write.

I've never been a professional, but I've been coding for nearly 30 years as an amateur, and I've "written" more code in the last year than the previous 29, and it was all tooling for my very non-tech small business. It's cut HOURS out of my week, and it's all software I could not have afforded to pay developers for. But with Lovable, just describe it and iterate.

What IS going to die is software as a service. I've cancelled hundreds of dollars a month of subs and rolled my own better tooling.

whackernews·5d ago

#ad

mattmaroon·5d ago

Yeah I’ve been commenting on here for 20 yrs just to promote some stuff later.

spicyusername·5d ago

That depression tells me you do.

uncivilized·5d ago

We’re all gonna be meat proxies

wartywhoa23·5d ago

That "we" is overreaching, I'm not going to be, for one. If that's the way of future IT, fuck that IT and that future.

slopinthebag·5d ago

throughout all of human history we've responded to technological progress not by stagnating but by raising the bar. i dont see why it would be any different today. technology + human will always beat technology alone.

estearum·5d ago

Throughout all of human history, humans were the substrate of value creation. When humans can be removed from the manual labor part of a problem, they are.

Now we're clearly entering a world where humans can be removed from the intelligent-problem-solving part of the problem.

How many more parts of problems are there?

system2·5d ago

Or come up with good projects that utilize these and provide services that Ai alone gannot provide.

margorczynski·5d ago

And what that would be? Prostitution?

system2·5d ago

I think large database-related projects. Ai context will never be billions of tokens. And prostitution on the side. With both, we will make a good living.

devinprater·6d ago

Good. Maybe they can use GPT-6 to fix the accessibility of their iOS app. Output shows as text fields to VoiceOver, and the accessibility announcements have backslashes before seemingly every punctuation mark. And then bring accessibility announcements to the Android app so I don't have to make a whole new app just to add that through an accessibility service. Ugh the things I do for accessibility cause I'm blind. On a better note though, AI has done so much for the blind community, from image (and increasingly video) description to mods for video games like Final Fantasy 1 through 6 Pixel remaster, I have a ton to be grateful for.

markerbrod·6d ago

Does anyone know if the ~50% price reduction also implies x2 subscription usage? Or is it only for the API.

Edit: Yes, it applies also to subscriptions, source https://x.com/thsottiaux/status/2102463847714247142

jrflo·5d ago

That’s great, I hate the opaqueness around subscription rates but at least it will show up in some way there too

NickHoff·5d ago

When I use these models in codex, there are two axes for me to control - the model and the reasoning level. I can use Astra, Sol, or Luna. And I can choose between 5 reasoning levels (light, medium, high, extra high, and ultra). What's the difference? As the problems that I want codex to solve get easier, should I turn down the model or the reasoning level? What's the difference between Astra medium and Luna high? So far I've just been leaving it on Astra and then turning the reasoning level up or down based on how hard I think the problem is.

altcognito·5d ago

I would describe it as "fidelity" and "verbosity" (or just amount of token generation to complete the task, sometimes that works out to scratch space, or literally how large the "solution" is).

If you have something that needs to be done right, might be a bit complicated, up the model size.

You can see this in the pelicans. Big model pelicans are pretty accurate by default. Up the reasoning and only more so, but with more detail. For Astra, it is 105 lines for low, 250 lines for max reasoning.

Small model pelicans will lack the fidelity of a large model. Bits will be out of place etc. For luna, it's 90 lines for low, 150 lines for xhigh.

Additionally the amount of time taken is increased for the larger models. Luna takes 11 seconds on low, and 1:33 for xhigh. Astra is 33 seconds on low, 4 minutes on max.

And naturally, there is the cost. There's some overlap in functionality between luna xhigh and Astra low in the sense that luna really can do quite a suitable job for some tasks. But there are just some tasks that just don't make sense for Luna, even at high reasoning.

The other thing to remember is that sometimes high fidelity isn't ideal. It can lead to overdesigning. My recommendation is to commit early, commit often, and review everything you do, which we've all been doing since before LLMs right?

sva_·5d ago

I mostly just use frontier models as well. Except for one case: when I let the cache expire (I think 5+ mins of inactivity) I'll switch to one of the cheaper models to summarize and write a handoff note, then pick that up with the better model. Picking up a session whose cache expired with something like 200k tokens with the frontier model reflects really poorly on your usage.

cbg0·5d ago

This is explained a bit in the API docs but you also have to adjust it based on your own tasks.

https://developers.openai.com/api/docs/guides/reasoning?api-...

miohtama·5d ago

For easy problems, just use Luna on max level. It has so much token mileage you can go forever.

brazukadev·5d ago

there is no correct answer for that. One is the difference in size/params. The other is the amount of "rounds" of reasoning generating and reviewing what is generated before the model decides it is good.

therealdrag0·5d ago

Ya it’s annoying to have to manage this.

But effort is basically how much extra internal scratchpad to use and how much extra questions to ask and answer before producing a result, Exploring more hypotheses, validating consistencies, calling more tools.

If you’re happy with your token spend on Astra then keep doing what you’re doing. but if you feel the need to conserve tokens, then you can do that by switching to smaller models like Luna when the task is straight forward.

Cu3PO42·6d ago

Cutting prices by 50% as compared to 5.6 prices is exciting. GPT-6 Luna at $0.10/Mio input tokens and $0.50/Mio output is positively insane.

EDIT: this doesn't say anything about availability on either Azure or AWS. I'm assuming it will show up later, but it would be interesting if it didn't.

manmal·5d ago

I’d rather keep 5.6 Sol, and get that even more optimized. I’m not sure I’ll like 6 Sol if it’s anything like Astra.

iyonn·5d ago

interesting. in my experience astra has been delightful to work with.

yreg·5d ago

Does API price cut translate into higher allowance on the subscription? Do we know?

manmal·5d ago

It does, usually. Luna seems like almost infinite on the 20x plan, and that’s reflected in the API price. Isn’t that the case for all providers?

whazor·5d ago

It is insane from a consumer point of view. Luna is cheap and smart enough to do many agentic tasks. Cheap enough so that you can put it on a website without auth.

motoboi·5d ago

already at azure foundry and copilot

c0rruptbytes·5d ago

they're already on bedrock

jjcm·5d ago

More image->html tests comparing Astra/Sol/Luna:

Design: https://image.non.io/78795662-8bfc-4e14-8d72-3738392aa6b3.we...

All 3 were given the same prompt to dynamically light these and to create the designs as a SPA with page transitions.

Astra: https://html.non.io/annui-astra

Sol: https://html.non.io/annui-sol

Luna: https://html.non.io/annui-luna

Luna gets the button wrong, and in the same way Grok/MiMo did. Looking into it more, it's because Luna actually searched my computer for similar builds, found the ones that I did for grok/mimo, and referenced their files. Astra is still the best by a significant margin in my eyes. Far more polish, better page transitions, effects that aren't overcooked and take into account the page. Better contrast.

wonnage·5d ago

The thin serifs not being slightly shifted to align weight-wise with the sans serif is triggering my OCD, but yeah Astra is miles ahead here

davidwritesbugs·5d ago

I think there must be such a thing as design dyslexia because they all look fine to me shrug

zeratax·4d ago

kinda interesting that sol and luna have the entire scene with dynamic lighting while astra only included the statue

alentodorov·5d ago

love this eval. keep making them.

yipinwong·6d ago

I've been raving about Luna 5.6 as it's dirt cheap, and "intelligent enough". Double quoted.

Now GPT 6 Luna is even cheaper, and more intelligent, there is no going back... to SOL 5.6 for intelligent layer.

dmazin·6d ago

Per the benchmarks in the post, Luna 6 is at best a couple points superior to Luna 5.6 and (unless I’m reading it wrong) xhigh has actually degraded in quality?

I was hoping for a serious Luna upgrade. It was already cheap enough. This feels more like a price reduction than an upgrade.

That said, if the new Luna is able to handle ultra mode and subagents v2 in codex cli, then at least that’s a win.

yipinwong·5d ago

Benchmark doesn't really show the whole story.

I forgot which model degraded in quality as time went by, but let's try out Luna 6 for a few more days to confirm for upgradability.

tripledry·5d ago

> Benchmark doesn't really show the whole story.

For me it seems like benchmarks are mostly noise, and the rest is based on vibes. Some find newer models annoying, some are amazed.

elcritch·5d ago

If you put Luna on Max it's still cheaper than Sol, but can achieve similar results. Though slower and with more iterations. Still it barely nudges my subscription usage!

yipinwong·5d ago

ty for the suggestion. I really never used "max/ultra" on Luna, and will give it a try.

wartywhoa23·5d ago

Ah, the ravers are not what they used to be anymore...

yipinwong·5d ago

Price is a big selling point for a normie like me.

stelonix·5d ago

It seems I'm one of the few Terra users since Astra dropped?

When 5.6 dropped I had no weekly limits and I could just drive my work with Sol xhigh and things were great. Once limits were back (and maybe token prices changed iirc) Sol was no longer usable (on Pro or business) unless I was ok with 4 prompts every 5 hours, so I had to switch to Terra medium/high. I've used Luna for some really dumb tasks like moving files, renaming variables and whatever other old-school refactors I've needed.

Then Astra dropped and it just uses so many tokens I've only prompted with it once. Now with GTP-6 Sol/Luna I'm not sure what's being said here but most importantly I'm wondering whether Luna 6 is a good replacement for Terra.

Has any other Terra user tried and knows more or less than answer to this?

NothingAboutAny·5d ago

I started off with Terra at first before reading anything basically just picking "the middle one" after a while of use I didn't really notice a difference between Terra-Medium and Luna-High, the benchmarks since have suggested there's no real reason to use terra because Luna is twice the speed and some fraction of a cost while on xhigh reasoning achieving better results than Terra medium

stelonix·5d ago

I remember trying Luna on high and finding it spent an enormous amount of time compared to Terra, but after your comment I will try it again and see how it performs. If you're correct, everything will change in my usage.

azuanrb·5d ago

Terra is in a weird spot for me. I used to run it as my main driver at medium/high, but after Luna's price drop and some experimenting, I switched to Luna xhigh. If I need extra juice, I just use Sol. Intelligence-wise, Luna xhigh is more than good enough for me. Speed is the only downside. Terra/Sol might be similarly intelligent, but they can get things done faster.

declan_roberts·5d ago

I just switched from Claude to openAI. I'm surprised at how much easier it is to talk to. Claude always spoke to me with a suspicious side eye as if I was trying to do something naughty. For example I could not get it to help me get an old abandonware game running (sim tower).

gizmodo59·5d ago

yeah I used to love claude! but these days it refuses and responds as if its like a big brother. glad competition exists and for the past few months codex has been significantly better. Even some oss models like glm are good but they dont have enough compute and get capacity constraints

sfkgtbor·6d ago

I'm glad both labs noticed and are trying to improve the models communication styles, they were getting closer and closer to meaningless gibberish.

reenorap·5d ago

Why do they bother creating effort to market all these different models.

All I want to know is how old is the model and how much does it cost. I can figure out which one I want to use based on that, assuming that newer models are always better.

Trying to convince us there is a difference between GPT-6-Sol and GPT-5.6-Terra or whatnot is ludicrous to the point of being insulting, especially when new models come out every week.

ecshafer·5d ago

price discrimination. They want to capture low and high cost agent requests, and different workflows.

ravenstine·5d ago

Seriously! Though I prefer GPT models to other frontier models, this shit is confusing. They keep changing the names of these models and they often don't communicate anything meaningful about the model itself, especially with these latest iterations. At least with "mini" and "nano" you understood they generally had differing speeds and "reasoning" capability, but what the hell do "Terra", "Sol", and "Astra" really mean? Which one of them is the effective successor to gpt-5.4-mini? It's hard to tell since the only objective information you'll get is token pricing. Is Terra less capable than Luna because it makes me think of dirt and grass? Or is Luna less powerful because the Earth is bigger than the Moon? Apparently that's the real answer. And why do I even have to think about this? And what comes after Astra? Galactica? Or will they start naming the succeeding models after different candy bars? Should I even care since a new model will get farted out mere days after I figured out what differentiated the last one?

What's unclear to me is who OpenAI thinks they're marketing to with this form of branding. These different models don't really mean all that much to the vast majority of people using their products who aren't developers, and developers aren't helped at all by the way they've been naming said models. Are they merely scared that they'll become irrelevant because Anthropic decided to give their models quirky names like "Opus" and "Fable"?

If OpenAI really wants to give their models names, they should name the generation of model and then have the different sub-models named by purpose or capability level. After all, I wouldn't use Mini for a job that Nano could easily do, and I wouldn't use Nano for a job that the full version of GPT-* necessitates. Similarly, I've had to discover exactly how Luna, Terra, and Sol are appropriate for different complexities and task types. OpenAI could help me skip a lot of those steps and just tell me what each model distillation is good for without causing me to look through their pricing page and make educated guesses. After all, shouldn't they not want me to pay attention to how much they're charging me?

All of this makes the days of frontend framework churn seem quaint and actually preferable.

wyre·5d ago

What models are good at is so subjective it isn't OpenAI's place to really say "Use Sol for X and Luna for Y". They are publishing benchmarks so you can figure out how to best utilize each model. I get that it sucks to have to do this yourself, but eventually there will probably be some type of benchmark that help with discovering a model's strengths and weaknesses

The issue that OpenAI had when they had mini and nano models is that ambiguous the differences between those and everyone just used the base model anyway. I have no idea what type of job mini can do that nano couldn't or vis-à-vis.

I do wonder if it would just be better if they were named 6-small, 6, and 6-big?

ravenstine·5d ago

> I have no idea what type of job mini can do that nano couldn't or vis-à-vis.

In my experience, Nano won't reliably handle complex open-ended tasks and is mostly suited for very explicit instruction that it can't screw up. It's no different from how there are some chores you can give to kids and there are other tasks you need at least a teenager for. If the decision tree of the task is very clear and conventional, Nano can be cheaper than giving the task to a relatively overpowered model, especially if it's something where the output is rigidly structured. This makes it well suited for skills that essentially run CLI commands and generate output, especially because it is usually faster. Mini is more like a discount version of the base model, and Nano is the dollar store version. Mini is more of a generalist and a fairly good deal if you have a moderately complex task that is conventional, but can be less conventional that what Nano can handle. I mostly used gpt-5.4-mini this year for my side projects because it's a pretty good generalist while significantly saving on costs. It is, however, somewhat dumber than the base model and more prone to ignore or forget rules you give it. I'd have just used a base model, but the low cost of Mini and Nano made them appealing to me. Maybe I'm a cheapskate, but I have hundreds or possibly thousands more in my pocket than many other users because of that.

This workflow I settled into with Mini and Nano didn't map cleanly on to the current generation of model tiers. With the price of Luna, you'd think it would be a replacement for Nano. In a sense it is, yet I didn't find that Terra became the new Mini. Terra is more powerful, better at explaining its own decisions, yet I've also found it to be relatively stupid while charging me more to use it. On the other hand, Luna with its reasoning set to "high" is what I consider to fill the role of Mini, and is good enough such that I no longer use Mini. Sol and Astra are great, but they're pricey. It could be my own brain and its bad perception, but so far I don't get the point of Terra. Luna succeeded at reverse engineering some abandonware with a very complicated licensing and virtualization scheme, and did so over SSH into a Windows VM with only PowerShell on the other end. Terra did such idiotic crap to my flashcards app that I stopped using it for anything after that.

This is why I find OpenAI's naming unhelpful and kind of pointless. I don't really care about the benchmarks that all these models are commonly run against. They're not that useful, IMO. OpenAI could easily give early access to these models, get a ton of feedback, and provide better insight to customers on how these things behave. Even calling Terra "gpt-5.6-overpriced-cheating-dumbass" would be better than wasting my time and money figuring it out myself. But that wouldn't make OpenAI as much money.

scrlk·6d ago

Artificial Analysis is reporting that 6 Luna scores 2 points lower on their coding index than 5.6 Luna, but is 60% cheaper:

> In the Coding Agent Index, Sol improves but Luna regresses: In OpenAI's Codex harness, GPT-6 Sol (max) scores 57 in the Artificial Analysis Coding Agent Index, up 2 points from GPT-5.6 Sol (max), with gains in Terminal-Bench 4.0 (43% vs 37%) and SWE-Atlas-QnA (58% vs 54%). At $2.99 per task it costs ~50% less than GPT-5.6 Sol (max) and sits on the Pareto frontier of Coding Agent Index vs Cost per Task. GPT-6 Luna (max) scores 41, down 2 points from GPT-5.6 Luna (max), with lower scores in SWE-Atlas-QnA (44% vs 49%) and DeepSWE v1.1 (64% vs 66%), at ~60% lower cost per task.

https://x.com/ArtificialAnlys/status/2102462962758033624

Given that they had to discontinue sales of the 20x Pro plan after the Astra release due to compute constraints, I wonder if 6 Sol & Luna are smaller vs their 5.6 counterparts?

scrollop·5d ago

Can we trust AA anymore after the last debacle a week or two ago?

anthonyrstevens·5d ago

Why is everything a "debacle". And people complain about Claudisms. sigh

6thbit·5d ago

wait what debacle?

wyre·5d ago

Probably referencing how when Astra came out it was only 1 point ahead of 5.6 sol.

Readerium·6d ago

Yup more like a 5.7 than a 6

jrflo·6d ago

The only two benchmarks shared between the Opus 5.5 and Sol 6 launch seem to be frontier code and automation bench, looks like Sol wins on automation bench (same performance for half the cost) and Opus 5.5 wins on frontier code (2-5% better scores across the board for same cost)

XCSme·5d ago

Also, Terra is gone, GPT-6 Luna is smarter than 5.6 Terra and costs *15x* less [0].

[0]: https://aibenchy.com/compare/openai-gpt-5-6-terra-high/opena...

adamrezich·5d ago

If I'm understanding correctly now when you want to use Codex to do a given task you need to decide between:

    GPT-6   Astra (low medium high xhigh max ultra)
    GPT-6   Sol   (low medium high xhigh max ultra)
    GPT-6   Luna  (low medium high xhigh max ultra)

And that's not even counting the GPT-5.x models:

    GPT-5.6 Sol   (low medium high xhigh max ultra)
    GPT-5.6 Luna  (low medium high xhigh max ultra)
    GPT-5.6 Terra (low medium high xhigh max ultra)
    
    GPT-5.5       (low medium high xhigh max ultra)

And then there's a fast mode toggle for all of it, too.

Not exactly a low-friction user experience!

Like are you supposed to just somehow intuit, “ah yeah, this task is definitely a GPT-6 Sol Medium task,” or something?

Is this just second nature for OpenAI employees? How are end users supposed to know how to optimally choose a model for a given task? Am I missing something completely here?

thimabi·5d ago

It’s confusing indeed, but I like having many options, particularly considering that pricing can be wildly different depending on the model.

Maybe OpenAI can offer an "auto" mode for Codex on the subscriptions, while leaving the possibility of users manually overriding whatever model the router chooses. To me that would be the best of both worlds. The problem is building a competent model router.

cruffle_duffle·5d ago

It’s a hard problem because among so many other things…switching models mid session because “shit got real” (or shit is now just executional) costs cache.

Alifatisk·5d ago

Avoid light and max. Stick to default model selection in Codex. Increase reasoning effort as you go. When the model fails on even xhigh, switch model and start from medium again.

ComputerGuru·5d ago

Wow, gpt-5.6-Luna was already a fairly unbeatable bargain and now gpt-6-luna is both cheaper and better. And they did a phenomenal job getting gpt-6-sol to max out right where Astra begins; funny how they just so happened to avoid cannibalizing their best model while still being quite cost-competitive near the frontier.

At least it sounds good on paper, the the graphed results do give me pause as it seems the lower cost might come from a slightly nerfed base model combined with more thinking, going by the more erratic scoring curves and the lower no thinking baseline score. I’ll have to try it out but I really hope they haven’t nerfed Luna/Sol to make this price point possible!

buckwheatmilk·5d ago

Looks like good one this time. Moving from fine tuned gpt-4.1-mini for structured outputs to gpt-5-mini made zero sense just because 5 was reasoning model and there was no way to disable the reasoning and it also did not have support for fine-tuning.

So essentially I was not able to get nowhere close to the accuracy of previous model and it was slower, and more expensive at the same time.

Now gpt-6-luna, has really competitive pricing and offers similar accuracy compared to gpt-4.1-mini fine tuned for my specific task. And fine tuned models are getting deprecated anyways, seems like a good time to move to gpt-6-luna.

yuretz·5d ago

I wonder what % of comments here are from bots.

phba·5d ago

Maybe I'm imagining things, but every HN thread about a new AI model seems to follow the same pattern, has the same arguments and talking points. The only difference is the version numbers of the AI models mentioned.

wartywhoa23·5d ago

No, you're not imagining, you're seeing a spade for spade. There's absolutely a template they keep rewrapping.

P.S. This cindyllm seems to be stalking me whenever I comment against the grain, does anyone else experience this?

I thought it should have been long dead of all the downvotes it gets, but there we go.

wartywhoa23·5d ago

No less than 80%.

droidjj·6d ago

Not only is GPT-6 Luna better, it's 50% cheaper. It was already practically free on a pro plan.

anelson·2d ago

I was very excited to try the new GPT-6 Luna on our internal evals for a cybersecurity application. The 50% cost savings over 5.6-Luna sounded like an easy win.

Unfortunately in our benchmarks 6-Luna uses way more tokens to produce the same result at a given thinking effort, and takes longer to do so. The additional tokens wipe out the cost savings for us. Has anyone else seen this?

mchusma·5d ago

My initial takeaway is that GPT-6 is mostly a lower cost win, for Luna. GPT-6 Max is an upgrade on intelligence too, but its mostly a cost play (which is great, not complaining).

Overall, I expect for most people think the winner of today was Anthropic. I personally am preferring Opus 5.5 at medium over GPT-6 Sol Max, in very very early tests. Similar price range, more capability.

But competiton is great, these are solid releases by OpenAI today.

cbg0·5d ago

Those two reasoning efforts are for entirely different classes of problems. I'd compare Opus Medium vs Sol High.

meerita·6d ago

OpenAI, Antrophic and others are operating with 80% margins. They can lower the prices for a long while.

thimabi·5d ago

You probably mean they are operating with 80% margins discounting training expenses, which will continue to be pretty high for the foreseeable future.

wyre·5d ago

Seeing how cheaply Xiaomi was able to train Mimo 2.6 I am starting to wonder if they are greatly over-exaggerating the real training costs to increase their valuations and investments.

desterothx·5d ago

that was rl, not training. its a fraction of the cost

anthonyrstevens·5d ago

Don't let facts and knowledge get in the way of a good conspiracy theory!

slekker·5d ago

Source?

system2·5d ago

Not a source but a comparison with a weaker non-SOTA model:

Nvidia's top AI chip Rubin sells in 72-GPU racks for about $3.5–7.8M. A rack running Xiaomi's MiMo V2.6 Pro generates roughly 150–300B tokens a day, worth about $130–260k at Xiaomi's API price. That's a payback of the infrastructure in a few weeks in theory. After a few weeks or a month, the only cost is electricity, and whatever they make after that is pure profit.

OpenAI and Anthropic are practically scamming people with the token prices.

wxw·5d ago

Most exciting part of this announcement is probably the pricing

  Model update               Input          Output         Reduction
  -------------------------  -------------  -------------  ---------
  GPT-5.6 Sol → GPT-6 Sol     $4 → $2        $20 → $10      50%
  GPT-5.6 Luna → GPT-6 Luna   $0.20 → $0.10  $1.20 → $0.50  50%

badatnames·6d ago

It's asking a lot to trust they can or will maintain this new pricing. In any case it's exciting to think this might lead to further price cuts in the highly competent and competitive Chinese clones. I'm still using ChatGPT for interactive queries, but at this point pretty much only because of its familiar UI

chaos_emergent·6d ago

Curious why you think it's unsustainable?

badatnames·6d ago

Because at some point keeping it up involves filing an S-1 that doesn't look like a garbage fire

wyre·6d ago

Didn't SpaceX already set a precedence for garbage fire S-1s? I don't think OpenAI has to worry about that?

badatnames·6d ago

SpaceX is a different beast with extremely high friction to enter its market, a massive technology lead, and well developed preferential high level relationships with just about every country worth worrying about.

OpenAI/Anthropic meanwhile feel a bit like they're hoping to sell iPhones in a market about to be flooded by $20 flip phones, with almost no channel of their own to do it. And for whatever mad reason OpenAI are now signalling they will attempt to compete on price with flip phones despite their cost of labour, energy, and just about everything else being far higher

wyre·5d ago

Wasn't SpaceX's insane valuation largely based off of Grok, because their rocket and satellite businesses could never be valued at over a trillion $$?

I don't see your metaphor to iphones and flip phones. This new Luna model is cheaper than deepseek 4.1 flash, except for cache reads. OpenAI having to compete with China is a much larger economic-political issue that is far larger than just our AI labs.

cmrdporcupine·6d ago

Well, they do rug pull constantly. This week and last leading up to this the cost to use Codex was overwhelmingly perceived as terrible. People running out of usage all over the place. Reddit full of people crying. I noticed it myself.

Then they do a new model launch, issue quota resets all around, and it's a party for 2-3 weeks before things return to normal.

FergusArgyll·6d ago

Oh, I'm happy I'm not the only one. Astra was feasting on tokens!

cmrdporcupine·6d ago

It wasn't just Astra. Sol 5.6 was a hog, too. They futzed with the formula and it pissed people off royal.

GodelNumbering·6d ago

Gpt 6 Luna is cheaper than Deepseek 4.1 flash! Today is wild in terms of intelligence/price across the board!

gizmodo59·5d ago

it was expected no? if cost is the only reason to use oss models, they can do much better than small providers who don't have much compute.

hehimself·6d ago

Love the price reductions across major players

madduci·6d ago

Because Qwen4 has been announced!

eloisant·6d ago

And GLM 5.3 works great

system2·5d ago

Except for the censorship. We use it for massive data crunching, and roughly 5-8% (depending on the day) gets censored and doesn't get a response. We switched to Mimo 2.6, which is relatively better. For censored stuff, we use Sonnet and OpenAI Nano models.

Also Mimo 2.6 is roughly 30% cheaper. Without batch.

Havoc·5d ago

What sort of content is it censoring? Politics I assume?

system2·5d ago

News mostly. Anything China-related gets censored without hesitation. Some random stuff got censored too. It is borderline unusable, to be honest, unless only numbers are crunched.

blovescoffee·6d ago

and to squeeze anthropic, and other research innovations, not just chinese models but those help bring price down

Readerium·6d ago

Opus 5.5 seems better? Can someone attach both scores

hehimself·6d ago

Not the direct competitor to Opus 5.5, cuz 6 Sol is 50% cheaper.

Readerium·6d ago

Same price on Cache Reads 0.2/M So won't be 50 percent cheaper, more like 25% cheaper assuming half cost is cache read.

blovescoffee·6d ago

cost is dominated by non cached reads

pinkgolem·5d ago

that might depend on usecase, half of my cost is cache reads usally

jdprgm·5d ago

I wish there was more transparency on the plus plans usage limits showing actual token usage and prices per model that eats away at remaining usage.

Does anyone know how exactly these price differences for example between sol6 and sol5.6 translate to codex percentages? In theory it seems like for "high" on both it should result in ~3x more usage. If that is actually the case it would be huge! But all we see is % left and % changes while using and we really have no idea when or how those numbers are being calculated or when they change. So there is a 50% price reduction on API but who knows how the hell that translates to whatever price calculation is used on codex.

cmrdporcupine·6d ago

Looking at their own charts it seems like it's only small incremental improvement over 5.6 Sol, but with a massive cost reduction. And the better writing/communication style that Astra had.

Which... fine, I'll take that.

cmrdporcupine·5d ago

Update: It's markedly worse than 5.6 Sol. It costs far less money because it's far far stupider.

jacobgold·5d ago

These counter-launches are starting to seem kind of tacky and boring. Just launch on your own schedule guys.

magarnicle·5d ago

Maybe this is what they meant by "pacing"?

goobatrooba·5d ago

> This year, coding agents have begun tackling tasks with more complexity, scope, and duration than ever before. At OpenAI, our internal usage has grown exponentially. Valued at API prices, daily token usage has exceeded $600 for the median researcher and $7,000 for researchers at the 90th percentile (Research acceleration: The view inside OpenAI ). As coding agents take on longer and more demanding tasks, the cost of sustained use matters more. GPT‑6 Sol and Luna combine strong coding performance with lower API prices, giving developers more room to iterate and teams the confidence to be more ambitious about what they ask Codex to take on.

Rarely have I seen such hogwash. It seems to be a mix of virtue signalling and trying to push the perspective that being "90th percentile" (on what exactly?) requires extensive AI use. You are telling me you expect each researcher to generate USD 7000/d or USD 140k/m in AI cost? Or is that a way to abuse tax laws in some way so they can claim their own payments for tokens as expenditure on the other side of the ledger?

redhale·5d ago

> being "90th percentile" (on what exactly?)

From context, I took this to mean 90th percentile in token usage. So yes, being a top token user does require extensive AI use.

jumploops·5d ago

I’m still finding context is king, even with the best models.

For example, I had Fable review Astra’s output yesterday, and it found some issues and fixed them. Passing the fixes back, Astra then uncovered additional issues with Fable’s fixes (and yes, this will go on ad infinitum if you let it, but these were “real” issues).

It seems the big story here is the reduced Luna pricing. It’s a fantastic model that can handle most automation needs (though I still use the big models for day-to-day development).

samuelknight·6d ago

No terra it seems? Luna 5.6 is great for token churning so it will be exciting to try the new one.

minimaxir·6d ago

Terra is the middle-child in more ways than one. It has much lower usage than Sol or Luna (going off OpenRouter).

MangoCoffee·5d ago

isn't Sol became Terra? this is OpenAI tweet: https://x.com/OpenAI/status/2102460975790137662?s=20

Astra is the best. Luna is cheapest then it seems like Sol is the middle child like Terra.

MrBuddyCasino·6d ago

Perhaps people realized that Luna Max is ~ Terra?

o_m·6d ago

Nah, Luna uses was more tokens and fills the context up way to fast. Terra is in the sweet spot where if feels like Opus 4.6. Competent but not too smart. It also lets you have longer sessions (back and forth) without filling the context too fast.

apitman·5d ago

Since I spent my morning fixing a bug in my OpenAI API proxy that completely broke prompt caching and caused my usage limits to burn like kindling, really happy to see some of their new cache tooling:

* Prompt caching dashboard: https://platform.openai.com/usage?usage_section=prompt-cachi...

* Adjust reasoning effort and tool availability without breaking cache