Previewing GPT‑5.6 Sol: a next-generation model

https://openai.com/index/previewing-gpt-5-6-sol/

by minimaxir • 26 days ago

1139 737 26 days ago

openai.com

System card: https://deploymentsafety.openai.com/gpt-5-6-preview

ChrisArchitect• 26 days ago

Pre-official discussions:

https://news.ycombinator.com/item?id=48678789

https://news.ycombinator.com/item?id=48683021

rvz• 26 days ago

Other than the worst naming I have ever seen (Sol / Terra / Luna), the pricing is still expensive:

GPT‑5.6 is priced per 1M tokens across three model sizes:
Sol is $5 input / $30 output;
Terra is $2.50 input / $15 output
Luna is $1 input / $6 output.

The OpenAI casino has never been more ready to take your money on gambling even more tokens.

minimaxir5• 26 days ago

Note that GPT 5.5 currently is $5 input / $30 output (short context) so Sol is in the same class, while Terra if the benchmarks are as claimed is indeed a half-price GPT 5.5 at comparable performance.

andrethegiant• 26 days ago

What don't you like about the naming?

lwansbrough• 26 days ago

I feel like going with Space + Latin is LLM-level creativity.

Edit: yeah. https://claude.ai/share/06fefe02-4299-44da-8c5a-42607f54ca77

arikrahman• 26 days ago

Can't buy cheaper as a selling point when Deepseek is basically free when hitting cache? Unsubsidized too, cloudflare and digital ocean can be the model provider for similar pricing.

Stitch42232• 26 days ago

With the $200/month plan I’ve never ran into any limits or issues. The product can be used every day for extensive sessions and development. What is everyone doing that makes them talk about tokens versus dollars?

minimaxir5• 26 days ago

If you've never hit the limits, why not do the $100/mo plan?

ai_slop_hater• 26 days ago

I ran out of usage using GPT-5.5 and had to buy a second subscription. I now switched to GPT-5.4 which is basically 2x usage.

fph• 26 days ago

But let's put it in perspective: what you're paying them is more than the average salary in many poorer countries.

kingstnap2• 26 days ago

Don't forget this.

For GPT‑5.6 and later models, cache writes are billed at 1.25x the model’s uncached input rate

Charging for cache writes is cringe and literally only Anthropic did it. Anyway this does mean the "real" prices are +25% on top of what you wrote there.

loufe• 26 days ago

"Next generation model"

If it was the next generation, why isn't it a major version change..?

ryangst_1• 26 days ago

LLM devs can't do version control

psychoslave• 26 days ago

Semantic is passé, word models moved to the next generation.

dominotw2• 26 days ago

vibe versioning

cruffle_duffle2• 26 days ago

To be fair, versioning has always been vibes based.

appplication• 26 days ago

Honestly LLMs are the ideal candidate for CalVer. It’s not like there’s any real API so there’s no backwards compatibility to maintain.

Even Apple adopted and standardized on it for their latest platform releases.

andy12_• 26 days ago

I think it makes more sense to make it so that major versions are different pretraining runs, and minor versions are simply the same pretraining run that was finetuned to different degrees. But it seems that that isn't cool anymore.

Kiro• 26 days ago

LLM versioning is entirely feelings driven. The ideal versioning is probably just names.

kaizenite• 26 days ago

Because if it sucks, they can just default to "It was a minor version change anyways"

goldenarm• 26 days ago

They could hold the GPT-6 name for the IPO

GTP2• 26 days ago

Some assume it was to try to slip under the radar and avoid being limited by the government as they did with Fable.

therepanic• 26 days ago

By all appearances, they did not succeed in doing so.

HarHarVeryFunny7• 26 days ago

AFAIK there is no difference between "generation" and "version". Version naming/numbering depends on how good it turns out to be, and competition. If the competition releases something then you need to push something out too.

Calling it 5.6 creates the least possible expectations, and therefore more potential for positive feedback.

The Sol/Terra/Luna naming is interesting. I wonder what Anthropic are considering for their next models? "Terminator", "Armageddon"?

wincy• 26 days ago

You gotta check out the new ChatGPT 6.3 Betelgeuse bro

rolph• 26 days ago

Heliopause

cyral• 26 days ago

If they called it 6.0 and it wasn't AGI, you'd see a lot of complaining here too

tasuki3• 26 days ago

What is AGI? (I know what the shortcut expands to, I'm curious about your definition. Don't the current models fit?)

ChrisLTD3• 26 days ago

If it's a new generation why isn't it GPT-6?

win311fwg2• 26 days ago

It does not introduce incompatibilities with earlier 5.x models? Frontier models are at a point now that there will never be a need for another major version bump, aside from those chasing marketing gimmicks. They are smart enough to adapt.

ChrisLTD3• 26 days ago

What would it mean to be incompatible with the other 5.x models?

peab• 26 days ago

not true. multimodality is still far from being solved

malnourish2• 26 days ago

A major bump will be warranted if/when we can truly separate prompt from data.

charcircuit2• 26 days ago

Why would incompatibilities have anything to do with a major version bump?

alcasa2• 26 days ago

They forgot how to do pretraining.

cleaning• 26 days ago

5.5 was a new pretraining run.

paxys14• 26 days ago

Given the expectations everyone has created GPT-6 has to pretty much be AGI.

tasuki3• 26 days ago

What is your definition of AGI that the current LLMs don't fit?

leumon• 26 days ago

We plan to make them more broadly available to people using ChatGPT, Codex, and the API soon.

I hope this means then fable will also get released again.

lanthissa• 26 days ago

why would it? if you're the us gov and sam&greg your good boy giving you 25m

and dario's you naughty boy who you dont agree with politically.

Let 5.6 free, keep fable chained and anthropic instantly sees rev loss and has to cave.

osti• 26 days ago

Sol? Looks like openai is jealous of anthropics good model naming ability and wants to emulate it.

dominotw2• 26 days ago

sol has no soul

taytus• 26 days ago

It's missing u

alcasa2• 26 days ago

They should have used Figher Jet codenames instead. The MiG-15 one has a nice ring to it.

arizen2• 26 days ago

Sol Goodman

MrCheeze• 26 days ago

TBF, they did it first with ada/babbage/curie/davinci. "Sol" is a much weaker branding, though.

ddp264• 26 days ago

I'm going to pre-register my prediction that GPT-5.6 Sol is significantly behind Claude Fable 5, as evaluated by general consensus once time has passed for people to get familiar with both.

hmate9• 26 days ago

What is this prediction based on?

gpm• 26 days ago

I suspect the same just based on their versioning scheme fwiw.

Onavo• 26 days ago

Fable is allegedly a massive model (estimates between 6-10+ trillion, with a few hundred billion active). If 5.6 is just an incremental upgrade over 5.5 (at the same model size) then it won't be able to fully compete with Fable just yet.

ddp264• 26 days ago

Based on my conjecture that Anthropic is ahead on AI research, and that OpenAI doesn't know how to make Fable-class models.

minimaxir5• 26 days ago

I suspect GPT-5.6 Sol will at-the-least be affordable.

MostlyStable2• 26 days ago

"Affordable" depends on what you need. When a task is able to be achieved by two different calibers of model, it's obviously more cost effective to use the less capable model, in the same way that you wouldn't hire a math PhD to do simple addition.

If what you need is only possible with the more capable model then the "affordability" of the less capable model is sort of irrelevant. If what you need is a novel mathematical proof, it doesn't matter that a high school student is "more affodable". You need the math PhD.

As "old" models get more and more capable, it's going to be an increasingly important skill to be able to adequately recognize when a task requires a frontier model and when it doesn't, so that the less capable (and therefore cheaper) model can be used.

Y_Y2• 26 days ago

Affordable? I'd settle for available.

dimgl• 26 days ago

why

chanbam• 26 days ago

Because he likes attention and wants to feel special

CuriouslyC• 26 days ago

Claude will win on "vibes" and it'll be close in coding but considering how incremental Fable is above 5.5 in terms of overall smarts, there's no way 5.6 isn't considerably smarter on the whole.

simianwords5• 26 days ago

I’m countering this prediction by stating that Fable and Sol will be somewhat similar - this has always been the trend and I see no reason why this should stop now.

HarHarVeryFunny7• 26 days ago

OpenAI may have a model in the works that is similar next-gen size and architecture to Fable, but this isn't necessarily it. I'd guess that 5.6 was more of a hasty reaction to Mythos - same base model (same size, same price) as 5.5 but with additional post-training to make it more competitive with Mythos/Fable in some benchmarks.

Mythos/Fable is supposedly next generation in size vs Opus, and is rumored to have some architectural innovation in terms of dynamic routing/compute, possibly only fully enabled with Fable which at $10/50 is still twice the price of Sol 5.6's $5/30, but a big reduction from Mythos preview which had been an astronomical $30/150 possibly due to the dynamic routing not yet having been enabled.

ddp264• 26 days ago

Is this the trend? There have been various points where one of Anthropic or OpenAI was substantially ahead. Sure, many times they're close, but now doesn't seem like one of them.

nharada• 26 days ago

Is that the correct comparison? Fable is twice the price

ddp264• 26 days ago

Fair point.

mccoyb• 26 days ago

When will GPT-5.6 Protomolecule drop? Me and the boys on Eros can't wait to get our hands on it!

slopinthebag4• 26 days ago

I'm excited for GPT-5.7 Pneumonoultramicroscopicsilicovolcanoconiosis, hope they drop it soon

dodslaser• 26 days ago

GPT-5.8 Llanfairpwllgwyngyll

da_grift_shift2• 26 days ago

For me, it's GPT-5.9 Year of the Whisper-Quiet Maytag Dishmaster

baq2• 26 days ago

Musk steals Dario and they both train Epic on Mars. US Space Force promptly finds oil on Mars and launches an armada in the next window. In the meantime rocks painted black drop on Mar-a-Lago.

Schiendelman2• 26 days ago

Oh man, here inside Ganymede I'm way more excited about the GPT-5.7 Io experiment! Hopefully it won't blow up in our faces!

static_motion• 25 days ago

Beltalowda!

bijowo1676• 26 days ago

Waiting for @simonw to report on this, before I read and try it

claudeIsDown• 26 days ago

I would love to see a more descriptive review from simonw instead of just SVGs generations.

simonw4• 26 days ago

I try! https://simonwillison.net/2026/Jun/9/claude-fable-5/ and https://simonwillison.net/2026/Jun/11/fable-is-relentlessly-...

lossolo4• 26 days ago

He is not an ML researcher or engineer, he is a passionate AI enthusiast blogger. He mostly does SVGs and other low effort checks (sometimes with major flaws, as people have pointed out a few times in the HN comments). Properly evaluating the model across all fronts requires a deep understanding of LLMs, how they work, the trade offs behind new architectures and the relevant research papers. It also takes a lot of time to build a proper evaluation framework so basically you can't just vibe code that if you want something that is solid.

simonw4• 26 days ago

You might be waiting a while, I'm not in that set of "a small group of trusted partners whose participation has been shared with the government".

minimaxir5• 26 days ago

The government doesn't have a Department of Vector Pelicans?

Imustaskforhelp• 26 days ago

I think that there are some OAI employees on Hackernews. I do believe that they should give access to ya, because after all it would allows us to generate pelicans :-D

What is the consensus on who becomes part of the said small group of trusted partners and if they weren't so opaque about it. I'd expect comparatively big names like Simon to be included within such but Alas its not reality.

realty_geek• 26 days ago

Come on openAI - add @simonw to your privileged team before the plebs start a revolution!!!

nsingh22• 26 days ago

I'm really getting sick of reading about safeguards and what I'm not allowed to do on every model release.

alansaber8• 26 days ago

New guardrails only allow you to code in rust. Just imagine.

low_tech_punk• 26 days ago

all the emphasis on cyber security. feels like a reaction to anthropic, not a real next generation.

tedsanders• 26 days ago

Yeah, we'll share a lot more details and evals when we can release GPT-5.6 widely. We focused on cyber (and bio) here to help explain why it's being held back for now. We would have loved to launch it to everyone - it's the best coding model I've ever used - and we plan to do so as soon as we can ('coming weeks').

(I work at OpenAI.)

jonp888• 26 days ago

So now have to be worried that I'm going to killed by an AI designed nerve agent that someone has cooked up in their shed?

FFS. I hate this world so much. I wish I could just flip a switch and never have to hear about or have anything to do with AI ever again.

Do you ever stop to think about the horrific dystopia you and your acolytes are creating?

sharksandwich• 26 days ago

how could that _not_ be the emphasis given what's happened with Anthropic and the Trump admin?

corygarms• 26 days ago

I'll buy that its next generation if the svg bicycle pelican is carrying a baby

MostlyStable2• 26 days ago

Wouldn't that be a stork?

HyperL0gi2• 26 days ago

Here is a trend I'm noticing:

- GPT-5 mini costs $0.25/$2 and will be discontinued in December.

- GPT-5.4 mini costs $0.75/$4.5 and is supposed to be the replacement.

- GPT-5.4 nano costs $0.2/$1.25 and, while it ranks better in benchmarks than GPT-5 mini, it's not even close when you test it in real scenarios.

So you're left being forced to go to GPT 5.4 mini if you use 5 mini today.

The same thing is happening here as their “Luna“ model will cost $1/$6.

Can't we just stay with the models we actually want? I don't need GPT 5.4 mini. GPT-5 does the job.

Maybe it’s the realization that it was never that cheap in the first place and they're forcing us to upgrade in a slow and painful way.

paxys14• 26 days ago

It’s the same as the SaaS model. Price keeps going up, and to justify it they keep forcing you to upgrade to new versions with features that nobody asked for.

theptip4• 26 days ago

“More intelligence” is the new feature. Almost everyone is asking for this.

Citation: have you looked at OAI and Anthropic’s customer growth numbers?

gonzalohm2• 26 days ago

Yeah, this is the classic silicon valley strategy of selling at a loss and then once they have captured the market inflate prices.

See Uber, Netflix, etc.

simianwords5• 26 days ago

This is a constantly repeated conspiracy theory and is not true at all. The api costs do increase but aggregate costs per task decrease. The question is: do people need lower intelligence models at all? The answer is a resounding NO!

How many people do you see using haiku or sonnet? I see very few and most people default to the latest model and just play with thinking effort. I think three layers are good enough and supporting more is not a good UX.

CraigRood• 26 days ago

I don't see them capturing anything at this point. If inference was profitable then they could compete on price/model and capture the market. Then increase price and pay back the model training.

Feels like they are just pulling in as much as they can whilst competing on capabilities instead. At which point its a case of who can last the longest.

Doesn't feel like Uber/Netflix.

neosat• 26 days ago

Good observations. There's definitely a trend in pricing increasing but also balanced by innovations and availability of other models (both open and closed) emerging as alternatives. It's natural for the labs to explore how much they can push pricing, and for competitors to explore how they can treat that margin as their opportunity to grow their business.

Eventually the pricing should be more stable.

benterix• 26 days ago

Eventually the pricing should be more stable.

Why do you think so? This game can be played forever, you just need strong marketing and orgs gullible enough to pay a higher price for a minor upgrade.

malnourish2• 26 days ago

Hardware hosting old models isn't hosting new models. If you want consistent models, host your own open weights ones.

wolttam4• 26 days ago

If you have no need for Anthropic/OpenAI's frontier model capability, you may be better served with an open-weight model that can't be taken away.

Edit:

GPT-5 does the job.

I bring up DeepSeek V4 Flash a lot on HN, but I want to mention that according to Artificial Analysis, it trades blows with GPT-5 (high) (from August, 2025) [0]

[0] https://artificialanalysis.ai/models/comparisons/deepseek-v4...

paxys14• 26 days ago

Unless you are hosting it yourself on your own infrastructure it absolutely can be taken away.

RALaBarge2• 26 days ago

It’s my daily driver in opencode

lmf4lol2• 26 days ago

We rolled out Deepseek V4 Flash to our customers and it was an absolute disaster, unfortunately. It was not able to follow simple commands, always "forgot" to do things, lied consistently about its work, and so on. It was pretty good though on on-off work, like summarizing something or executing simple commands, so we are experimenting now with using it for subagent work with clear instructions and hand off.

Deepseek V4 Pro on the other hand is a really really good main driver and we have a lot of success using it. Its not Opus or GPT-5.5 level but on its way. Kimi 2.6 as well btw.. so there is already quite some choice.

ai_fry_ur_brain3• 26 days ago

Deepseek V4 flash is actually useless. Sorry I've tested it after seeing so many comments like these. On Open router when trying to get it to output tool calls for creating tables, instead of providing the structured output correctly it was sending me peoples dropbox links and other image sharing site urls that led to pictures of random tables...

Llms seem to only impress a certain type of person. Hint, this type of person also was really excited about NFTs.

127• 26 days ago

DeepSeek V4 Pro is only ~3-4x as expensive as Flash. It won't replace GPT-5.5 (nowhere near) but I've been using the $20 sub to punch through tough cases and use Pro for rest.

lionkor3• 26 days ago

deepseek has no part of their privacy policy on their API about training. They are 100% training on every single word you give it.

If your customers are fine with that, your IP is not interesting, then you can use it.

simonw4• 26 days ago

On Nano "it's not even close when you test it in real scenarios" - what have you seen? What kind of things can GPT-5 Mini handle that GPT-5.4 Nano cannot?

isamu_2000• 26 days ago

We’re using GPT-5-mini in an enterprise data-processing workflow, and we too see that GPT-5.4 nano performs materially worse for our requirements, roughly 30% worse as measured through our test suite.

barrell2• 26 days ago

Also can confirm gpt-5.4-nano was unable to even keep up with 4.1-mini. Had to move off of OpenAI once 4.1-mini was retired

cyanydeez2• 26 days ago

No, you can't. These companies have two infrastructures: model training and model inference.

Inference needs to cache, it can't cache random model data, so it's essentially dedicated; it can't spin up models on demand, it has to know what demand is coming.

These companies are going to end up with very few models offered and that's probably generous. They might end up with just one model and you pay for removing it's safe guards.

sourcecodeplz• 26 days ago

who tf would use mini when you have dsv4 flash

tosh• 26 days ago

discontinuing the cheaper options is a risky move for openai

will trigger re-evaluations of models by other labs + inference providers

HyperL0gi2• 26 days ago

I can speak for myself. We are exactly at this moment trying to replace GPT 5 mini with an open weight / open source model. No luck so far.

mistic92• 26 days ago

Its happening to Anthropic Haiku and Gemini Flash/Flash lite. All of them are increasing prices and deprecating cheap models.

mchusma2• 26 days ago

I've struggled with this. You definitely can have great cheap models. There are many of them open source and served profitably by neo-clouds. The big labs have basically given up on cheap models, and it is frustrating. It means applications are not likely to build as much on them anymore (we are shifting workloads from Haiku/Sonnet to Deepseek v4, for example).

I suspect the problem is that they need to charge a lot to keep revenue numbers up, and they are more worried about cannibalizing themselves than others cannibalizing them.

mips_avatar• 26 days ago

I think it's more that they're abandoning simpler AI tasks to chinese models. Qwen 35b and deepseek flash are better than gp5 mini on my tasks and way cheaper.

theptip4• 26 days ago

Maybe it’s the realization that it was never that cheap in the first place and they're forcing us to upgrade in a slow and painful way.

All the analysis I have seen points to frontier models being profitable to serve. It’s using 50% or more of your GPUs for research plus CapEx for capacity expansion that makes these businesses so heavily cash-negative.

What you are observing is downstream of another detail. It gets more expensive to serve a model as utilization goes down. Plus the opportunity cost vs newer, more-profitable models.

There are plenty of valid reasons to critique here. “OpenAI is lying about this being a sustainable price to serve” is not one of them.

barrell2• 26 days ago

There is really ample analysis pointing to inference not being profitable, look at anything Ed Zitron has reported.

btbuildem• 26 days ago

stay with the models we actually want

If you want control over the models you use, you have to self-host.

hadlock• 26 days ago

Each model release gives an opportunity to reduce the number of old models still on offer, and charge a higher, less-subsidized tier. The trick is to charge a subsidized price that is less than an M3 Ultra, so they continue paying you rent, instead of a one-time fixed cost. So far open models can't compete with Opus 4.5 but as soon as it can, people will be looking at buying devices that can run that model locally.

We are a claude shop but we already bought two mac studios to start migrating less complex but still agentic workflows there. We will break even on those in less than a year.

fouc2• 26 days ago

Breaking even in less than a year? What's the math on that?

CSMastermind• 26 days ago

5.5 is smart enough for 99% of my tasks. I need that level of intelligence at ever decreasing prices.

aleksandrm• 26 days ago

I don't know about Cursor or other outlets, but I use GPT 5.4 exclusively in Windsurf (Sorry, Devin!), and it's a very capable model that doesn't break the bank!.

abc123abc123• 26 days ago

No. Welcome to the wonderful world of SaaS. If you want your gui, your terms, your software, self-host.

But I think, in time, a new generation will relearn this truth.

zeryx• 25 days ago

Why not self host or go to openrouter if you don't need SOTA frontier?

jeffybefffy519• 24 days ago

Gemini has done the same thing, gemini-3.5-flash is 15x more expensive for input tokens than gemini-2.0-flash. They are forcing us up the pricing ladder by deprecating the old models....

thesurlydev• 26 days ago

Not really news until it's widely available.

Anyone know the latest around Fable being re-released after gov smackdown?

mekpro2• 26 days ago

We need more coding benchmark score. Not sure that winning terminalbench 2.1 alone is a clear win over Fable/Mythos yet.

Y_Y2• 26 days ago

But they are the only ones who can benchmark, so the best and only benchmark will be the one where they win. It's just business baby.

jdw6412• 26 days ago

I think GPT writes code the best. How well will it write in version 5.6? It gives me chills.

Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT.

So using GPT brings both fear and excitement.

The fear comes from realizing that this level of code is now the average for most people. The excitement comes from knowing that I can now study and learn at this level too.

I'm really looking forward to seeing how much more advanced the code will be with the upgrade to 5.6.

seviu• 26 days ago

I am on the opposite camp. Open models are starting to perform better. GPT 5.5 keeps on messing things up.

On the contrary, pi + glm + DeepSeek… bliss.

Fable was a different kind of beast though. Rip.

arizen2• 26 days ago

Ditto on GLM 5.2 + DeepSeek V4 Flash combo.

For most important work (complex, cross-domain inquiries etc.), I still rely on Codex GPT 5.5 though.

enraged_camel2• 26 days ago

> I am on the opposite camp. Open models are starting to perform better. GPT 5.5 keeps on messing things up.

I'm working in a 600k+ LoC codebase that has complex domain-specific logic and lots of moving parts. I find that Codex 5.5 is pretty good at surgical fixes, but does not go out of its way to explore and figure out what those surgical fixes might break. So I only use it to work on parts of the system that are pretty isolated from everything else so that risk of regression is small.

baq2• 26 days ago

Yeah, Opus/GPT need multiple rounds of reviews from each other to get to clean auto review. Fable was like, it is done and indeed… crickets in bot comments. ‘No issues’ galore.

whalesalad• 26 days ago

GPT-5.5 has been really hard to beat imho. I've spent $$$ on Opus, Deepseek v4 Pro and recently started to dogfood GLM-5.2 (which is not bad) but I cannot really trust any of them (almost blind) like I can trust GPT-5.5. It gives me tremendous confidence. I cannot say the same for any of the others I mentioned.

square_usual• 26 days ago

Every time I use opus these days I go shut up... you are not fable.. Hard to imagine how just three days with it changed how I saw LLM use.

baddash• 26 days ago

how much does your setup cost you? just curious

sanderjd5• 26 days ago

How are you running glm and deepseek? Local or hosted? If the latter, where do you run it?

pawelduda• 26 days ago

How do you judge what is a good or bad thing to learn from a LLM? So you don't have to unlearn the bad bits later

jdw6412• 26 days ago

When I searched for papers on using LLMs, I found that typically, you can have an LLM generate code and then ask it to find GitHub projects similar to that code. Then you can learn by looking at the pull requests and seeing how they structure things In the old days, if I wanted to understand why memory offsets, padding techniques, or data layout structures were written a certain way, I had to stare at a senior programmer's code all day or wait for them to reply. But LLMs, while they do flatter me, explain things at a level I can actually understand. And LLMs don't get annoyed.

jdw6412• 26 days ago

There's a lot of tacit knowledge in programming.

-Why do you cut API boundaries this way? -Why do you change the order of struct fields? -Why do you deliberately insert padding?

Most of it depends on the background and context. Sometimes you add it, sometimes you don't. To understand this tacit knowledge, you need access to senior developers. But their attitude often depends on how promising the student is and what background they come from. On top of that, you don't have to rely on the respondent's mood, authority, or availability.

Programming is fundamentally a field that requires seniors. In my case, I had no such seniors at all. I learned to code by buying codebases from failed companies and studying them. My first job didn't hire me as an employee—they hired me as the CEO of a subcontracting company (because that was structurally more advantageous for the contract). So I wasn't given the patience to learn programming fundamentals gradually. I had to pay penalties if I failed. Most of the projects I worked on were the kind where failure meant bankruptcy for me. Naturally, there was no one to teach me.

Most of my knowledge comes from reverse-engineering the code I purchased.

People say LLM code contains falsehoods, but commercially sold code has always had falsehoods too. Honestly, if we're just talking ratios, LLM code has fewer falsehoods.

In that sense, I still think it's a matter of context. If LLM code is false, was human code ever really true? LLMs do lie. They generate plenty of incorrect code. But humans do the same thing. If a problem comes up, you just look it up then and there. For me, LLMs and humans aren't all that different.

HarHarVeryFunny7• 26 days ago

I'm suspect on how much of a coding advance it will be.

Seems odd that their announcement has zero coding benchmarks, with the closest related thing being terminal bench.

artursapek• 26 days ago

They claim extreme performance on ExploitBench, which Mythos was touted as being incredible at. https://x.com/OpenAI/status/2070555278576439306

jdw6412• 26 days ago

Maybe I'll know once I try it? Honestly, for small functions or methods, I don't think there's a huge difference between models. But the larger the code gets, the more noticeable the difference seems to be.

Personally, I think this kind of coding experience varies from person to person

vanuatu• 26 days ago

sadly with all the labs benchmaxxing I feel like you just have to try the model for a while to really evaluate how good it is, especially for each individual use case

hereme8883• 26 days ago

Tracking model performance on Artificial Analysis makes me think these models are constantly optimized/tuned in some way or another. GPT 5.5 was scoring in the mid 60's when it was first released, now it's almost 10 points higher.

MangoCoffee• 26 days ago

zero coding benchmarks

"What gets measured gets managed"

stagger87• 26 days ago

I even referenced multiple code bases on GitHub

Well, GPT referenced every GitHub code base, no wonder it won! :)

fatata123• 26 days ago

No offense but have you considered the strong possibility that you’re just not good at what you do? I am occassionally pleased but mostly annoyed or disappointed… but never getting anything close to chills. That sounds downright weird.

adamtaylor_13• 26 days ago

No offense but have you considered the strong possibility that you're just holding it wrong? You're entitled to your opinion, but OP is hardly the first person to say something like this and is surrounded by tons of folks saying the exact same thing. Just because it sounds weird to you, doesn't mean it's not true.

cmrdporcupine• 26 days ago

"no offense..."

... then says offensive thing.

jdw6412• 26 days ago

You're not wrong. But programming isn't something only talented people do.

Xenoamorphous2• 26 days ago

Another strong possibility is that you might be working on something that’s not very prevanlent in the training set.

Even the choice of programming language matters, e.g. Java or Javascript vs some niche one.

8bitsout• 26 days ago

Is it possible for you to provide examples? What were you trying to solve? What was your solution and why was GPT's solution superior and faster?

ignoramous• 26 days ago

... why was GPT's solution superior and faster?

Not saying that's the case with OP, but I've found folks sometimes just rationalize it so [0] as they're paying top dollar for it (especially, when compared to may be less capable but affordable models).

[0] https://en.wikipedia.org/wiki/Choice-supportive_bias

lionkor3• 26 days ago

Not trying to be mean but it's likely the case that OP is not evaluating this properly, either due to a lack of skill or a lack of objectivity

Topfi4• 26 days ago

Purely subjective, but I tend to prefer reading Opus 4.8 output over GPT 5.5 code, even when the latter can have a higher overall ceiling. The former is just a bit more convenient to review.

Razengan2• 26 days ago

Codex 5.4/5.5 has been great for me as well compared to Claude Opus.

I've been mostly using it for Godot/GDScript code reviews, rubber duckying, asking it for better ideas for naming stuff (one of the hardest problems in programing)

I still can't trust it for generating code for entire files/classes/projects, because it's still icky, creating unnecessary variables and functions, using multiple `if`s instead of `and` or `or`, but it's good enough for generating Mac/iOS apps for my personal use in SwiftUI because fuck trying to keep up with Apple's documentation, or even migrating ancient Visual Basic stuff I made as a kid up to SwiftUI :)

So using GPT brings both fear and excitement.

Only excitement for me. I've never been more productive, not because I ask AI to make something for me, but it helps me make what I was already going to, but better and quicker.

AI like any other tool could help smart people be smarter and dumb people be dumber, rather kinda like Toklien's Ring: You could be Sauron or you could be Bilbo or Frodo, or you could be Gollum :)

NothingAboutAny• 26 days ago

For me in Game dev, codex has a habit of checking every argument for null and then silently early exiting the methods when true. I have explicit instructions for it not to do this - but it still does. I haven't done any c# outside game dev but I have no idea why people would want their programs to silently fail.

lnrd• 26 days ago

I think GPT writes code the best. How well will it write in version 5.6? It gives me chills.

Heard this exact sentence multiple times a few months ago about Opus 4.6, then 4.7 and 4.8 were considered a disappointment and today people miss "the good old times of 4.6" (referring to a few weeks of February 2026).

Very fascinating to look at all of this unfolding.

dannersy2• 26 days ago

Reading this thread makes me feel like I'm taking crazy pills. The folks on this train in my team do not produce anything significant that we can rely on or use. A lot of hollow prototypes that join the prototype graveyard and code that needs extra scrutiny on critical areas ultimately leading to taking longer.

It's a shame, they were smart and productive engineers. Now? I guess everyone is just all-in on the slot machine.

noveltyaccount• 26 days ago

I prompted Codex 5.5 to one shot something where I wanted the design to have a pluggable decision module. I gave it a few examples of the kinds of inputs and actions I expected. I did not constrain it beyond that high level of what I wanted. The design it came up with was very good. Easily on par with what any senior engineer at big tech would. And cleanly decoupled in a way that would make future refactoring simple. I was damn impressed.

sanderjd5• 26 days ago

I have long felt like "out of the box", I really dislike gpt's coding style. It seems really verbose and likely to write way too much error handling and wordy comments and worse at finding existing functionality to reuse rather than writing everything from scratch. This has been relatively easy to mitigate with prompting, but I still find it annoying.

YMMV I guess!

jdw6412• 26 days ago

I think you could be right. I do use excessive error-handling code and verbose comments — that's true.

But most of my time is spent on delivery, and the biggest problem with delivery is that if a bug occurs during runtime, the client curses me out. So to me, GPT code feels meticulous.

Open source contributors might be different. Most of them write code after long periods of deliberation. They take their brightest ideas and put them into open source. Those pieces of code are probably the best answers those programmers can give.

But for someone like me, who works primarily on delivery, we mostly plug in proven patterns and focus on getting things done. 'It works' and 'it's beautiful' are different terms, after all. In that sense, I highly value the meticulousness of GPT code — the very thing you called verbose. Because even if it's inefficient, at least it runs, and it catches and wraps around far more of the parts where things break.

Given a month, I could probably write code at GPT's level, at least to some degree. The problem is the difference between one hour and one month. At its core, AI code is still based on training data.

mschuetz• 25 days ago

I haven't tried the latest Codex but I switched from GPT to Claude because I think Claude writes much better Code. GPT's code ends up way more verbose/complex/overengineered than it needs to be.

arendtio• 26 days ago

I didn't know that I was color blind, but thanks to those charts, I think I need to see a doctor...

I mean, you can read them even without the colors, but who on earth thought that those are a good set of colors? Oh, I forgot it was probably someone on 'Sol'.

throwaway0123_52• 26 days ago

I mean, you can read them even without the colors

I'm not colorblind and I was depending on the textual context implying Sol was better than Terra. I had to zoom in quite far to actually differentiate between the colors.

If they insist on terrible colors would it be so hard to differentiate by marker shape or line dashing too?

da_grift_shift2• 26 days ago

    Flagged activity can also trigger account-level review across relevant conversations and risk signals, consistent with our terms and policies around content retention and review. Looking beyond a single conversation helps our systems distinguish persistent malicious behavior from legitimate dual-use security work, where similar technical concepts may appear in very different contexts.

Fascinating!

Every conversation you have with these "more capable" models will be monitored and joined up and then your entire account might one day be tagged as Distiller or Cyber Threat Actor or whatnot. When combined with identity verification (which isn't discussed in this press release), expect people to be falsely flagged and banned from ever using OpenAI models again.

Wish I could find the thread from last week where discussions of exactly this kind of thing were dismissed as daft and outlandish.

paxys14• 26 days ago

falsely flagged and banned from ever using GPT models again

That would be the best case scenario. More realistically a few wrong prompts is going to get you on a government list, and if you’re an immigrant some dark cell.

alansaber8• 26 days ago

... they have been doing this the entire time

mohsen12• 26 days ago

Additionally, we’re introducing a new `ultra` mode that goes beyond the capabilities of a single agent by leveraging subagents to accelerate complex work.

I'm curious about how does this work? Do the subagents also get to use the same tools? Will the client be flooded with tool calls? Why extra pricing for a new "model" when the same thing can happen in the client with more controls?

And if it's an army of subagents, why do they compare it to Fable and Mythos? Those models with similar harness would probably bench better I'm guessing

simianwords5• 26 days ago

Claude also has ultra code mode which is exactly the same thing. This seems to be different from pro however.

derwiki4• 26 days ago

Don’t all the major harnesses (pi, Claude code, codex) utilize sub agents? Def if you direct it to, but I’ve seen at least pi spin them up without explicit instruction.

alansaber8• 26 days ago

Absolutely yes

te_chris• 26 days ago

With pi they’re an extension, but that’s pi

alansaber8• 26 days ago

I'm shocked they didn't use subagents already. Maybe they're just talking about their web deployment being unified with codex?

helloplanets2• 26 days ago

Deep Research has been using the Orchestrator -> Subagents -> Synthesizer loop since the beginning. It's just strange that they'd put a loop benchmark next to actual model benchmarks.

Maybe it's a tune of the base model that works especially well with the subagent loop?

Sidio2• 26 days ago

With Codex, subagents are only used if you specifically prompt for them. Unlike Claude Code. Odd since it's the former with excess compute available to them.

gck13• 26 days ago

If it's anything like ClaudeCode's ultracode, it's nothing new or revolutionary.

It's essentially a bunch of subagents being called by a deterministic script written by the main model thread, each eating tokens for lunch and output of which is synthesized by an orchestrator agent.

mohsen12• 26 days ago

Confusion is: ultracode is not a different model with its own benchmarks

enraged_camel2• 26 days ago

> If it's anything like ClaudeCode's ultracode, it's nothing new or revolutionary.

OpenAI flat out copying Anthropic is a pretty funny development. It's strong evidence that they've been in catch-up mode.

Sidio2• 26 days ago

The fact that it's even named Ultra is pretty telling.

jamilton• 26 days ago

Yeah, I'm interested too. My guess for the reason, if not purely to eke out more performance, is so they can cleanly gather real-world data on this kind of usage.

rolisz• 26 days ago

If it's anything like Claude Ultracode, it burns 3 million tokens in half an hour with a single prompt.

koolala3• 26 days ago

Sounds like an Agent using an Agent like Mr. Meeseeks.

jiggawatts• 26 days ago

Will the client be flooded with tool calls?

I was just saying to colleagues that I haven't felt the need to go past an 8 core machine until this month, when I started running parallel GPT 5.5 agents on a decent sized codebase (over 4 MB of code). There were times I could barely move my mouse cursor!

duggan• 26 days ago

As part of our ongoing engagement with the U.S. government, we previewed our plans and the models’ capabilities ahead of today’s launch. At their request, we are starting with a limited preview for a small group of trusted partners whose participation has been shared with the government, before releasing more broadly.

The clowns in the US administration can barely remain coherent from one sentence to the next.

Having them be the gatekeepers of technological progress in 2026 is fucking lame.

anukin• 26 days ago

Most administration is like that. The optimization h happens at the delegation to the competent.

submeta• 26 days ago

Are GPT 5.5 and Opus 4.8 the last models we're going te be allowed to use in Europe? Is there going to be a cut, and we're only be allowed to use less capabale models outside of the US?

I mean, if they deem Fable 5 to powerful to share with the rest of the world, what's left for us?

alansaber8• 26 days ago

We have le chaton fat, worry not

algoth13• 26 days ago

That's a real possibility for a time, but eventually people will look back at fable 5 the same way we look back at gpt2

vatsachak3• 26 days ago

All of these LLMs are getting better at being at an LLM

But GPT-5.5 is as useful an LLM can be; it has solved lemmas I've thought about for a year, it can implement typed STLCs in Rust when I give it a formal grammar, it can help me analyze Postgres planner dumps.

It's great at tasks that have short solutions but

- they cannot learn based on a project

- their long term planning capabilities are worse than worms

- they are unconfident in decision making

- their internal representations are disgusting compared to JEPA

- they don't have any "system clock" like humans and computers do

- LLM architecture is not modular like computer architecture or human brain architecture

There's so many issues with LLMs. I wish that companies can start working on the next generation of architectures before the bubble pops

derwiki4• 26 days ago

Totally agree! They also conflate things all the time (a major type of hallucination) and IIUC that can’t be solved with the current architecture, just patched over

esafak• 26 days ago

- their internal representations are disgusting compared to JEPA

You say this based on a theoretical understanding or did you inspect them?

vatsachak3• 26 days ago

Look at VLM mechanistic interpretability papers vs just pca on JEPA trained weights.

JEPA gives you interpretability for free.

I have not personally inspected them and my view is maybe a more exaggerated/dramatic claim of those working in the JEPA sphere

gulbanana• 26 days ago

Fable had very confident decision-making and would push past obstacles that Opus finds daunting :(

ddwrll• 26 days ago

What happened to the nano/mini/standard/pro naming scheme, which worked perfectly fine and is intuitive to understand? Why does OpenAI insist on having the most inconsistent and confusing model and product names possible?

I'm looking at you Codex.

00deadbeef• 26 days ago

It’s still easy to understand as the more capable the model the bigger the celestial body they’re named after.

simianwords5• 26 days ago

Thoughts

1. Naming convention is copied from Anthropic and honestly is more catchy than a number (amongst normal people)

2. How in the world did Anthropic have to do all the theatrics about Mythos just to have OpenAI release an equivalent or stronger model a month later without any drama???

3. Cheaper models are just don’t fit any usecase imo and OpenAI knows it so they keep increasing the floor - I’m still convinced task per capability is reduced with each release

4. How in the world would open source models keep up with the multi layer security? Either this security is all theater or we will finally see a ceiling in open source models because by definition they can’t have those protections

5. Cybersecurity things are boring to me because it’s all zero sum cat and mouse games

chrishare• 26 days ago

1/ Agreed, better naming convention and model layout 2/ It isn't, there would be many more comparison benchmark results if it were, but also - theatrics may be marketing 3/ Disagree that cheaper models don't have a place 4/ Do they need to keep up? 5/ It's boring until something you own or run gets compromised, I guess, but even then - this is preview of things to come (biosecurity, etc)

AlexCoventry• 26 days ago

How in the world did Anthropic have to do all the theatrics about Mythos just to have OpenAI release an equivalent or stronger model a month later without any drama???

Corruption. Giving Trump $25M will earn you a favorable decision.

woeirua• 26 days ago

The choice of the name Sol is interesting for those Raised By Wolves fans out there… “Praise Sol!”

firasd• 26 days ago

Some interesting stats here about the current landscape https://arena.ai/leaderboard/agent

Agent Arena (Dynamic ranking of models on how well they orchestrate tools for real-world agentic tasks, based on signals like tool reliability, task completion, and steerability.)

Top 10, Highest rank to lowest

Claude Fable 5 (High), Claude Opus 4.8 (Thinking), GPT 5.5 (xHigh), Claude Opus 4.7 (Thinking), GPT 5.5 (High), Claude Opus 4.7, Claude Opus 4.6, GPT 5.5, GPT 5.4 (High), GLM 5.2 (Max)

Text Arena View overall rankings across various AI models in text-to-text tasks across math, coding, creative writing, and other open-ended domains.

Top 10, Highest rank to lowest

claude-fable-5, claude-opus-4-6-thinking, claude-opus-4-7-thinking, claude-opus-4-6, claude-opus-4-7, muse-spark, gemini-3.1-pro-preview, gemini-3-pro, claude-opus-4-8-thinking, gpt-5.5-high

mydreamof2• 26 days ago

there is no GPT 5.6 init, so what's the point?

dakolli2• 26 days ago

The only real world task benchmark I know of is Scale Labs RLI

https://labs.scale.com/leaderboard/rli

Its clear to me these models are useless on any real world task, a 4% pass rate on $20-30/hr Upwork tasks. This whole trend of agentic engineering is a giant money grab.

vessenes• 26 days ago

Missing some recent models on that list, but I think most crucially, the harness is fixed —- one of the major learnings of the last few months is that harness and eval (“looping” and support / tooling around it) is really critical. I would guess these numbers are the floor.

For instance, some of these tasks include creating videos, and one of the common reported failure mode is truncated videos, or not all videos being created. This sort of failure mode is currently best managed by an outer evaluation loop; no frontier model will, when managed by an eval loop, submit work like this right now.

nnevatie• 26 days ago

these models are useless on any real world task

I beg to differ. They are not perfect but immensively useful today.

andrewlin247• 26 days ago

they're trying to be anthropic with these model names

rappatic• 26 days ago

Seems like OpenAI has succumbed to the urge to give their models catchy names like Anthropic does

derwiki4• 26 days ago

Why not? I’d bet most HN readers don’t know what GPT stands for

alansaber8• 26 days ago

GPT is kind of a stupid name when you stop and think about it.

smeeth• 26 days ago

The sooner the USG figures out a standard process for approving releases the better. There are many differing opinions on how much to regulate AI, but I think we can all agree ad-hoc policy sucks.

meetpateltech• 26 days ago

Another model family, another naming scheme to get used to.

Sol Ultra ≈ Pro

Sol ≈ Standard

Terra ≈ Mini

Luna ≈ Nano

alansaber8• 26 days ago

AI marketing washcycle is very efficient.

paxys14• 26 days ago

There are 3 models. Ultra is just a reasoning setting.

ALittleLight2• 26 days ago

I hate not being able to use the latest models. There needs to be a much faster resolution to whatever is happening with the federal government.

stuckkeys2• 26 days ago

How else is this administration going to make money?!? How dare you...if they do not accept bribes...what is there left for them? This is a premium buy...First one to beat competition gets the worm. So, you pay Trump, trump gives you access...then you pay subscription to SAMA lol.

SubiculumCode2• 26 days ago

lol. It's about national security and the worry is real, even if the administration is a dangerous clown show.

stuckkeys2• 26 days ago

How is it about "national security" if only select have access to it? lol come on

HarHarVeryFunny7• 26 days ago

[flagged]

dang2• 26 days ago

"Don't be snarky."

"Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something."

https://news.ycombinator.com/newsguidelines.html

jimmydoe• 26 days ago

Is there a list of Gov-approved companies?

If this is the new norm, we as workers should all start look for jobs in those companies.

mikkelam• 26 days ago

Would love to see benchmarks on cognition's FrontierCode

johnnyApplePRNG• 26 days ago

Doesn't it strike anyone as strange that SOL, TERRA, and LUNA are all quasi-scam crypto tickers?

alansaber8• 26 days ago

There is a crypto ticker for literally any catchy short string.

Maxatar• 26 days ago

There's also Fable coin, Mythos coin, and Opus coin all of which predate the Claude models.

Heck there's Fart coin, Harambe coin, Dog Wif Hat coin, you name it coin...

bluepeter• 26 days ago

I feel a bit like a Soviet hearing about Levi’s or the latest Springsteen release. C'mon!

OsrsNeedsf2P• 26 days ago

Like Mythos before it, I'm simply not excited about a model I can't use

sigmoid102• 26 days ago

At least they plan to give the public all versions. Feels infinitely better than whatever the hell is happening at Anthropic.

"Yeah, we've got the absolute best model out there. Trust us. Truly scary."
"O-ok? May I see it?"
"Gtfo. Here's a worse version of it for you plebs."
"Um, thanks?"
"Lmao, actually no. The current admin fell for our scare marketing. Here, have this even worse crazy expensive token burner that gets more hardware limited every week."

You can say what you want about OpenAI, but their corporate strategy feels so much more solid.

mchusma2• 26 days ago

I don't see this as that different. Anthropic was the first one to get involved in the "AI models must be approved" regime. OpenAI just has the advantage of being second.

(To be clear: I do not like this new paradigm)

m3h• 26 days ago

If GPT-5.6 preview is not available outside US government approved "trusted partners", I don't see how the General Available can be trusted later.

Who knows what they will fix, block or change in the model between the preview and GA time. Open models can't arrive soon enough.

speedgoose• 26 days ago

Open models arrived. They are not even that far behind anymore. But the hardware costs are a bit too high for now.

supermdguy• 26 days ago

We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed.

This is really exciting. I work on voice AI, and we're still using 4.1/4.1 mini since none of the frontier models come close on latency. I'm excited to be able to have more interactive experiences, I think it'll unlock new ways of working with these models.

MitziMoto2• 26 days ago

Also building voice agents and have found GPT 5.4 with no thinking to be the sweet spot for latency vs intelligence vs cost.

GPT 5.5 with no reasoning is actually slightly faster, and much smarter, but too expensive.

What I'm really looking forward to are the next gen speech to speech models. gpt-realtime-2 is almost there, but not quite good enough for our use case. 5.4 actually beats it on answer latency even cascaded with stt/tts.

totalhack• 25 days ago

What is the latency you are seeing with 5.4 no reasoning? And where have you landed for stt and tts solutions?

nopakos• 26 days ago

People where mocking EU for regulations and now this is happening in the US. I know that Europe is behind in AI but still...

dgellow2• 26 days ago

The EU has regulations, the US doesn’t, it’s whatever Trump and his cultists decide

Invictus02• 26 days ago

Are cyberweapons/cyberattacks "munitions"? if so, then isn't a machine capable of producing those munitions also itself a munition? I don't think you can put this down to "orange man bad" or "regulations", we're dealing with a genuinely groundbreaking technology with clear military applications

mistercheph• 25 days ago

if so, then isn't a machine capable of producing those munitions also itself a munition?

You mean, for example, a computer?

sowbug• 26 days ago

https://news.ycombinator.com/item?id=48690510

gandreani2• 26 days ago

Easily the most interesting part of this announcement is buried in the second to last paragraph:

"We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity."

750 tokens/s on a frontier model is going to be extremely interesting. I doubt this new version is anything but a version bump in terms of capabilities but if we can start getting these answers back faster, they end up being more useful.

Just off the top of my head, I can think of the tedious task of finding certain functionality within a codebase. I usually can't beat an AI agent harness at this task today. If the AI model is 3x faster I have less of chance.

helloplanets2• 26 days ago

OpenAI also announced two days ago that they're starting to make Cerebras style chips themselves [0], will be interesting to see how fast SotA model inference will be by the end of the year.

[0] https://openai.com/index/openai-broadcom-jalapeno-inference-...

WarmWash• 26 days ago

Cerebras is different than what jalapeno is.

Jalepeno is for mass scale inference.

Cerebras is extremely expensive and difficult to scale, hence the limited release.

jauntywundrkind• 26 days ago

I don't see any indications that OpenAI is doing wafer-scale work.

I tend to doubt they would. Cerebras notably doesn't have a kv, is wildly high bandwidth, but within/across the chip, not able to dump/restore kv super well. I doubt openai is going to build something that is as expensive to run. Also, wafer-scale is absurdly hard & weird to pull off, so I doubt that would be their first foray.

mlyle• 26 days ago

I don't understand how you refer to this as "Cerebras-style". Cerebras is wafer-scale and unique. Jalapeno is an inference-optimized conventional chip.

paxys14• 26 days ago

Even if their chip is a difference maker, end of the year is wayy too optimistic. It’ll at minimum be a multi-year effort to bring it to production at scale.

sberens• 26 days ago

For comparison, openrouter says opus 4.8 is ~55 tokens/s and fast mode is ~102.

750 tokens/s for their largest model is going to be nuts

gandreani2• 26 days ago

Using gpt-5.4-mini in off-peak hours already feels like super-speed to me. That's probably no more than 100-150 tk/s. I can't imagine 750!

I've always eyed Cerebras but never had a use for it that would justify paying for the API directly. Although now that I think about it, trying out the API would probably cost less than a subscription for a month...

order-matters• 26 days ago

the more advanced models also utilize a lot more tokens, and a lot of these extra tokens may go towards safeguards at a higher rate than prior models as well.

not to say a speed boost isnt there but if they didnt increase tokens / s at all youd likely see things slow down a lot with the new model compared to current

windexh8er7• 26 days ago

What about 15k tokens per second? [0] I remember looking at this earlier in the year and it being so fast that it feels fake. And, yes, this model is old - but still awesome for what it is.

[0] https://chatjimmy.ai/

comboy• 26 days ago

But it seems that there is some queuing/load balancing on their side, I mean when opus is actually outputting this 55t/s it feles fast, but apart from it's internal reasoning I think there's sometimes just waiting.

xnx• 25 days ago

"up to 750 tokens per second"

Emphasis on "up to". Imagine whatever limited situation (e.g. pre-cached query) and that will probably be the only time it hits 750 tokens/sec.

tontinton• 26 days ago

Yep this is a glimpse into the future of 500+ t/s, which is in my opinion the next big thing that validates Jevon's paradox (the models are already smart enough)

devmor3• 26 days ago

“Smart enough” really depends on how many other people have encountered a problem close enough to yours and solved it somewhere on the open internet, IMO.

Most of the frontier models can, when prompted and tooled correctly, do a lot of “reasoning” tasks that amount to resolving how the user has explained a particular widely known paradigm.

The more difficult and obscure the issues you provide them with, the faster you notice them reward hacking by altering the criteria until they are no longer attempting to solve the problem. Using “advisor” style loops helps hold this off at the cost of tokens, but there is still a fairly short limit at which they will essentially give up if they can’t find all of the necessary information - sometimes the issue is actually worse if they find a small amount of information instead of nothing - they’ll extrapolate from that tiny piece of data and generate plausible-sounding hallucinations almost every time.

And god forbid your problem involves doing something a different way than the majority of people do it. Unless you can write a full spec on it, the models will repeatedly spiral back into adjusting everything about your problem until it matches one of the most popular approaches in their training data.

paxys14• 26 days ago

Faster tokens = more reasoning loops, so it can actually make the models smarter as well.

digitaltrees• 26 days ago

I think the glimpse that is there will be exclusive access. So much for the open in openAI. If this technology really transforms society in the ways expected with inequality an unavoidable consequence equal access should be required like internet access was (isp can’t give preference to specific user traffic)

cruffle_duffle2• 26 days ago

"we can start getting these answers back faster, they end up being more useful."

Dude, 10x token speed is going to be absolutely nuts. Half the "parallel subagent workflow" business seems to be driven simply as a means to avoid tapping your thumbs waiting for the infernal robot to finish something. If things come back speedy quick all the time, it should keep up with the "speed of the human" and let me stay focused on one thread instead of half a dozen. Plus the cost of screwing up gets significantly lower because you just re-fire with an adjusted prompt and iterate.

Someday these things will be 100x as fast as they are today and that is when things will get insane.

Terretta• 26 days ago

it also makes the parent brain-dead because all those subtokens are missing from the context thus unable to steer the hyper dimensional context driven generation, and the subagent is dumb as a post so synthesizes something very weedsy while you're specifically attempting to understand the forest

eli3• 26 days ago

I'm skeptical of how fast "up to" 750t/s really means. Maybe if they make it extremely expensive so it frees up enough capacity?

GPT‑5.3‑Codex‑Spark currently runs on Cerebras chips and it's giving me around 150t/s. Still relatively very fast, but nowhere near the 1,000t/s they claimed at launch. (Also it's not a very good model.)

That said, I'm super bought in to faster models being better for most use cases than smarter models.

beering5• 26 days ago

Soon the bottleneck will be how fast your laptop can grep for a string.

aurareturn• 25 days ago

If it's 150 t/s, that's barely faster than Nvidia GPUs who are batching a lot more and are a lot more cost effective. Add in the Groq piece and Nvidia claims it can do 400 tokens/s.

donquichotte• 26 days ago

I can think of the tedious task of finding certain functionality within a codebase. I usually can't beat an AI agent harness at this task today.

Yup, I remember "racing" the AIs to figure things out in codebases just a year ago. Today, I have no chance. Whether it is due to degraded reasoning capabilities on my part or better models, I don't know.

abustamam• 26 days ago

At least in my case, much of the code in the codebase I'm working on is AI generated so even if I have an accurate mental model of how everything works, I have no idea where any of it is located or named.

kalstone• 26 days ago

AI is always going to be able to write a grep statement faster and more accurately than a human

DonHopkins• 26 days ago

Now start thinking, if possible.

https://www.youtube.com/watch?v=43QHhEfzz-Q

motoboi• 26 days ago

bean in mind that "GPT‑5.6 Sol on Cerebras at up to 750 tokens per second" not necessarily means the same model (in terms of inference result). It can mean anything like a very quantized model, a different level of model activation per inference etc.

Of course we can trust that wouldn't name the same thing with different levels of intelligence, right? Right?

beering5• 26 days ago

yeah but it’s trivial to just try it out and compare.

lostmsu• 26 days ago

Does the Cerebras variant offer input caching and corresponding discounts? Last I checked Cerebras would not cache or would cache but not give discounts for the cached input, making it impractical for agentic use and multiturn conversations.

swalsh• 26 days ago

This would be amazing for some of our "real-time" workflows, that need to fallback to AI for one reason or another. What used to happen is a rules based system did the majority of work, and occasional corner case would fall back to humans. Then we moved AI in, still not real time, but much faster. Cerebras could make that even faster.

bob1029• 26 days ago

At a certain rate we will be able to move towards continuous / real-time inference systems. The discrete, turn based solutions are quite confining with how they must be trained. Continuous and real-time would fundamentally alter the domain.

From an information theory perspective we are still in dial-up territory with regard to the actual information rate. 750 tokens per second would be a really bad dialup connection. Imagine 10 millions tokens per second.

dennisy• 26 days ago

That would be interesting.

Do you feel most of the speed upgrade will come from the software or hardware side?

mikepurvis2• 26 days ago

Is there anyone exploring or writing about this in public? I've felt for a while that the turn-based model was not quite right, but also felt too stupid and ill-informed to have much of an opinion about what else it could be.

ai_fry_ur_brain3• 26 days ago

Ahh yes slop at the speed of light, how useful!

b1125• 26 days ago

Your comment made me think of another real time. Real time, dynamic code/apis.

Imagine a world where there is no code, just things mildly handshaking and then creating data APIs on the fly. Where communication is fuzzy and locked in on an individual basis. No years of RFCs, no RFCs at all, just... data.

Just data, man.

An API arbitration aberratically assigned at authorized access, abridged and annotated, analytically assuring absolute assurance.

nyrikki2• 26 days ago

We still have the problem that auto regressive decoders are memory bound.

The new Blackwell hardware combined with TensorRT-LLM and speculative decoding consistently can hit 1,000 TPS/user barrier, comparing to closer to ~250 TPS/user (out of 10k+/TPS on the server)

Is there something I missed, this looks more like 14.4 to 56 on a 64kbps backing channel modem story. I have no doubt that there are still massive gains to be found, but they seem to be using existing constraints more efficiently, not that fios is coming.

I don’t have the budget to work on the foundational model scale, but with a draft model 10x–20x faster than target and an 60-80 acceptance rate I can see how they could promise 750/TPS (with a lot of other hard work) but I would appreciate where I should look to figure out what I am missing.

dyauspitr3• 26 days ago

And more importantly those 10 million tokens/s should cost fractions of a penny. Tokens need to be dirt cheap so I hope they build out massive solar+battery powered data centers asap.

ai_fry_ur_brain3• 26 days ago

From what I know about batch processing/ concurrency in inference this is a pipe dream... Or its going to cost an arm and a leg. I think they're lying or its going to be a much smaller model and not "frontier"

kolinko8• 26 days ago

You have speculative decoding that easily increases speed 2-4 times with no loss of quality, and of course MoA architectures that speed up inference 10 times or more, although with some quality loss.

Better hardware, and other techniques on top of that and you speed up even further.

qznc• 26 days ago

https://mikeveerman.github.io/tokenspeed/?rate=750&mode=thin...

This is what 750tps looks like, I guess.

buddhistdude3• 26 days ago

Just to think what this will look like in a couple of years.

amluto2• 26 days ago

That’s an awful visualization. I can skim code quite quickly, but not when it shows up one character at a time in a small window, modem style.

At least that site should draw out a full page then start replacing that page with the next, starting from the top and working downwards, repeating each time it hits the bottom.

me-vs-cat• 26 days ago

You get used to it. I don't even see the code. All I see is blonde.. brunette.. redhead.

TacticalCoder• 26 days ago

I usually can't beat an AI agent harness at this task today. If the AI model is 3x faster I have less of chance.

Yes: we have these new tools that are extremely good at helping us search through our codebases. Not just to find where/how functionalities are implemented: IMO bug searching is even way more powerful.

But: why would you want to compete with AI to do that? I cannot compete with grep/ripgrep... And I'm cool with that.

This lets you focus more on the more interesting parts, where AI/LLMs suck fat balls.

_fat_santa• 26 days ago

I still use GPT-5.3-codex-spark which also runs on the Cerebras chips. Spark can run at >1000 tok/s but it's highly limited in it's context window size so it's not suitable many workflows.

Granted this will be a bit slower (relatively speaking) but it will still be awesome.

philip1209• 26 days ago

Same - I had some "AI-assisted coding interviews" where I had to bring my own AI tools, and found the speed of codex-spark to be important for making progress quickly (and not sitting there waiting on Opus to think for 10 minutes).

js2• 26 days ago

second to last

There's a word for this that you should never pass up an opportunity to use: penultimate. (You should also never pass up the opportunity to use "defenestrate," but it sadly does not apply here.)

kolinko8• 26 days ago

A friend of mine had his visa accepted because of this. He was explaining what he plans to do in US and he threw in “penultimate” into a sentence somewhere.

The council stopped him, said that if he knows such words he definitely won’t overstay his visit to work as a dishwasher, and accepted his B1/B2. Seriously.

Not sure if it would be the same if he used “defenestrate” when talking about his plans.

v-erne• 24 days ago

> penultimate

Oh that's a word I haven't heard in a while. And I know it mainly thanks to Monty Python great sketch:

https://m.youtube.com/watch?v=l9Aj7W3g1qo

linzhangrun• 26 days ago

I saw videos of coding with Mimo-V2.5-Pro UltraSpeed, which is advertised at 1,000 tokens/s, which is very impressive.:

https://www.bilibili.com/video/BV1fME16uEW7

If the time-to-first-token latency also greatly improved, this could be very useful for end-to-end in controls, like autonomous driving for example.

trollbridge5• 25 days ago

It’s awesome, particularly since it’s at DeepSeek tier prices (3X of DS-V4-Pro). At 1,000 tok/sec though you can really rip through tokens. (About $9 an hour if you manage to run the output nonstop.)

It tends to cost more than DS since it doesn’t seem to have as many input cache hits.

nop17• 26 days ago

3x faster burn than 3x expensive token, generate more tokens, more fees

jeswin• 26 days ago

At thousands of tokens per second, LLMs (harnesses) can start to do a broader tree search of possibilities even in inefficient token space. This unlocks capabilities outside programming.

yiyingzhang• 26 days ago

It all depends on the context window size. A small context size with fast performance won't be very useful today, as most workloads (like requests behind codex) usually have very long context.

Cryptosale752• 26 days ago

Cerebras is Milli Vanilli. They spend 10 years burning cash on a failed idea (which is frankly insane, since they should have figured out the limitations of heir stack in like... a weekend) and struck accidental gold with their 'Giant ass wafer'.

The company is valued like they broke open the grail, when in reality it's more like they bought a Cybertruck, got it stuck in the mud, and realized "You know what this thing does better than all other cars... shovel mud"

I'm shorting Cerebras with margin to virtually zero.

easygenes• 26 days ago

This is a strange one. We know the hardware capabilities of Cerebras force them to do aggressive REAP pruning to serve Kimi K2.6. Meaning that about 750B parameters is the upper limit of what they can serve economically. Not sure if this means Sol is smaller than anyone thinks or that they're just going to charge so much that a very inefficient serving regime is feasible.

Avery29• 26 days ago

The speed sounds great，faster models make that gap much more visible..

qnleigh• 26 days ago

Last I heard, Cerebras chips were entire wafers and would be extremely expensive. How could OpenAI possibly have enough of these to serve a popular model at scale?

kingreflex• 26 days ago

this means they also earn at a faster rate in some setups :)

trollbridge5• 25 days ago

This is something Xioami already did with MiMo-2.5-Pro a month ago, and at a higher speed (1,000 t/s).

750 tps at GPT-5.5-Pro prices would be ruinous!

_boffin_• 24 days ago

That statement gives a lot of insights into the possible model size. Llama 3.1 405b runs @ ~900t/s: https://www.cerebras.ai/blog/llama-405b-inference

From initial vibe research (which is totally not correct by any means) ~13.5k concurrent streaming clients capacity

swe_dima• 26 days ago

Pleasantly surprised that it costs as GPT 5.5, thank god for the competition.

simianwords5• 26 days ago

No comments on the cerebras version that might finally enable intelligent voice mode instead of being stuck with 4o-mini class

scrlk• 26 days ago

Sol, Terra and Luna

So the next naming scheme might be FTX, Madoff and Enron? :^)

czk• 25 days ago

steady lads, deploying more capital

hereme8883• 26 days ago

Seems like OpenAI's strategy to release models after Anthropic has been paying off.

Is it just me, or does it seem like Anthropic has been more of a pioneer the past few years, and OpenAI tries to copy features they like?

khurs• 26 days ago

OpenAi dropped what they called 'side quests' like Sora [0] after Anthropic pursued a strategy of targeting software engineers.

In many companies, it's IT who will have major input into which company they sign up with as non-technical leaders need guidance, and by making IT fan boys of Claude Code, the enterprise contracts followed.

[0] https://builtin.com/articles/openai-side-projects

GodelNumbering2• 26 days ago

I do not like the fact that this forces people to remember one more hierarchy of "Sol vs Terra vs Luna". OpenAI was supposed to simplify their naming since at least 2025.

willmarch2• 26 days ago

The Sun is bigger than the Earth which is bigger than the Moon.

GodelNumbering2• 26 days ago

There are infinitely many 3-level hierarchies. My point was about overloading the model sizing with one more unnecessary classification.

micimize• 26 days ago

Haven't we established defensive and offensive security usage are intractably entangled? I.e. "patch all [security] bugs, make no mistakes" gives one a list of potential exploits to hand off to less capable models.

Doesn't that undermine all good-faith discourse on cybersecurity safeguards, controlled usage etc? Or is that overstating the case (I'm not a security researcher myself so kinda parroting).

masonwan• 26 days ago

Guess it's just another price bump hidden behind output token speed.

zkmon• 26 days ago

It appears that between GLM-5.2 and GPT-5.6, anthropic is feeling the heat, atleast in the bang-for-the-buck heuristic?

datakan• 26 days ago

Can only hope. Anthropics usage caps are horrible

sim04ful2• 26 days ago

This seems like it would be the largest and first closed-source model Cerebras has offered till date

ComputerGuru3• 26 days ago

Codex Spark models already run on Cerebras

mekpro2• 26 days ago

codex spark is not large model though, much weaker than standard model.

sim04ful2• 26 days ago

Sol and 5.5 pro are in parity at $5 input / $30 output. What I'm inferring from this is that: - model weight size didn't change, and this is mostly a result of better model architecture and scaled up RL - better hardware utilization and and they're making better margins OR - worse hardware utilization and they're okay with digging into their margins.

paxys14• 26 days ago

The space is mature enough that pricing should largely be disconnected from underlying training cost. Basically, they are selling it for $X because that’s what the market expects the latest Pro-level frontier model to cost.

coder543• 26 days ago

5.5 Pro is $30 in / $180 out: https://developers.openai.com/api/docs/pricing

I think you meant 5.5.

I agree it is probably the same size model. It's probably exactly built on top of 5.5, just with more training, or else they would have bumped the version number to 6.

moomin• 26 days ago

The language used in this press release is borderline hilarious. It’s simultaneously trying to tell you how great it is while also telling it’s not THAT great. Nothing to worry about, move along.

anentropic• 26 days ago

Previewing <minor version bump>: a next-generation model

snthpy• 26 days ago

Exactly. If it's next gen then why is it 5.6 and not 6?

lionkor3• 26 days ago

An LLM wrote the announcement

dang2• 26 days ago

All: for comments on the policy side please go to this related thread:

U.S. government will decide who gets to use GPT-5.6 - https://news.ycombinator.com/item?id=48690101

ericyd• 26 days ago

whoa, a new model that surpasses benchmarks of other models? wild.

wonkyfruit• 26 days ago

TLDR - It's not quite Mythos but it uses about 5 times less tokens, and those tokens are also cheaper?

https://pbs.twimg.com/media/HLwuJLvbwAAOfQZ?format=jpg&name=...

laurels-marts• 26 days ago

And much faster!

BoorishBears• 26 days ago

For GPT‑5.6 and later models, cache writes are billed at 1.25x the model’s uncached input rate, while cache reads continue to receive the 90% cached-input discount.

Not them joining Anthropic with this bullshit. *

Caching infrastructure is already a leaky abstraction over a feature that is not as reliable or debuggable to the end user as it should be, charging for the 'privilege' of interacting with it is really annoying.

(* for reference on 'this bullshit': ChatGPT previously didn't require anything special for a basic level of caching. Unless you wanted extended cache times, it'd just "do the right thing" and try to use nodes that had your prefix already cached in memory)

kingstnap2• 26 days ago

This is basically just a 25% price increase being done subversively. Usually you do need caching.

seaal2• 26 days ago

Did GPT-5.6 Sol Ultra decide the terrible colors for the benchmark graphs?

throwaway0123_52• 26 days ago

I was wondering the same thing. From textual context it is clear enough that Sol should be above Terra, but I had to zoom in really far to actually differentiate between the colors and I'm not colorblind. I saw a light mode version of the plot on twitter that was better but still not great.

OpenAI's plot design has been consistently awful and inaccessible, it seems like they're optimizing for something other than readability because I find it hard to believe they aren't putting in any effort for such major announcements. If the colors have to be awful they should at least differentiate with marker shapes or line dashes.

At least it isn't as bad as the stacked bar chart where the 50-something bar was higher than the 60-something bar.

Topfi4• 26 days ago

I remember them using these chart colours during the 5 launch, maybe even 4.1 back in the day. Don’t know why, maybe its their CI manual that’s been generated by gpt-3.5-turbo…

JohnRoseDev• 26 days ago

I can’t help but think that these benchmarks are completely fake. Sam even posted a benchmark on X a couple days ago of how the ‘complete version’ of 5.5 cyber was already ahead of Mythos apparently. This just feels like absolutely fake nonsense. The impact of Mythos on the industry was clear and in front of everyone’s eyes. The amount of vulnerabilities Mozilla fixed. The vulnerabilities and exploits Anthropic showcased in that blog post about the chrome sandbox escape etc. And now we’re supposed to believe this 5.5 cyber is already ahead of Mythos, ok. And yeah, gpt 5.6 is even further ahead, alright.

brookst• 26 days ago

Well if they are posting fraudulent benchmarks, that's a good sign to invest in their IPO. It's pure downside protection: IPO does well, profit. IPO does poorly, concrete evidence of pre-IPO fraud.

I personally don't think it's likely that OpenAI would post completely fake numbers in this pre-IPO period, but if you do, this is an opportunity.

throwitaway2222• 26 days ago

Sun Earth Moon

dainiusse• 26 days ago

I looked at the charts and it is clear that 88% from OpenAI is more than 88% from Anthropic.

ant-kinesthetic• 26 days ago

How much dynamic routing do we think is being done here, especially in light of the cheaper options be 2x less cost than 5.5. I think learned routing is interesting because it could be the case that it only works as a way to get token and cost efficiency for in distribution tasks (like these benchmarks), yet on real world scenarios it could trend towards the same cost as the Sol cost.

throwitaway2222• 26 days ago

Time to create more LLM based startups.

  * House design plans from prompts
  * Government surveillance of public communication
  * Extracting world/spatial concepts from language models (do we really need a world/spatial models now?)
  * Driverless City planning startups
  * Election vote rigging/harvesting startups
  * Video game NPC backstory startups (all NPCs in GTA 6 go to work, go home, shower, go to sleep now?)

Keep moving don't doom.

NetOpWibby• 26 days ago

How are they able to compare with Fable when Fable was only available for three days?

Topfi4• 26 days ago

Terminalbench numbers are publicly available. What is more interesting, why is that the only benchmark they highlight. Maybe 5.6 isn’t that far ahead of Fable 5 in DeepSWE and FrontierCode (which I consider the most useful and close to my evals + subjective experience)…

hodgehog112• 25 days ago

Yes, they only report the most saturated benchmark, which they were already very strong in before. It is very clear this model is nowhere near Fable, unfortunately.

Topfi4• 26 days ago

Is this a new pre training run independent of 5.5s or post trained on it with Cerebras support and a rebrand of Pro mode at more usable speeds as Sol? The latter seems more likely to me, especially as 5.5 scales very well across its modes so separate branding could make sense, but I don’t see any clear information either way.

kissgyorgy• 26 days ago

    we expect substantial benefit for legitimate defensive work, while meaningfully constraining prohibited offensive use.

That's literally impossible. Writing an exploit agains a known vulnerability needs the exact same knowledge that defending against the exploit of the same vulnerability.

Also just making the model better at code is just making it better to writing offensive code.

phplovesong• 26 days ago

Is there any model that rivals Opus or Fable? I would like to try something else, as Anthropic is pretty suss.

SubiculumCode2• 26 days ago

I hear this all the time, but in my opinion,they have acted as the most responsible frontier lab, taking their responsibility seriously. In fact, I do wonder whether openAI's large PR budget is about stirring up anti anthropic sentiment

ComputerGuru3• 26 days ago

“ Terra has competitive performance to GPT‑5.5 [while being 2x cheaper]…”

To me that means “it’s an inferior product but marketing dictates we try and hide that.”

And “our most robust safety stack to date. We strengthened protections for higher-risk activity, sensitive cyber requests, and repeated misuse, and spent multiple weeks finding weaknesses, pressure-testing our system, and hardening it against real-world attacks” is of zero value to me at best, and most likely to my detriment (increasing refusals or nerfing utility). Why do providers keep leading with that? Are there customers (besides support ChatGPT chatbot users, maybe??) that ask for this?

goobatrooba• 26 days ago

Maybe that message is for investors.

typpo• 26 days ago

> Terra has competitive performance to GPT‑5.5 [while being 2x cheaper]…
To me that means “it’s an inferior product but marketing dictates we try and hide that.”

I interpret this to mean you're about to get today's mainline performance at a fraction of the price.

dakolli2• 26 days ago

Its just lies by OpenAI dude, these people are just trying to IPO so they can buy a 100m yacht.

adithyareddy• 26 days ago

If that was the case they would have said "equals" or "matches". Instead they say "competitive", as in win-some lose-some.

dcre• 26 days ago

That message is obviously aimed at the government. See the other thread.

beering5• 26 days ago

The point of Terra is to be cheaper than the best model while being pretty good. Of course it’s inferior in intelligence.

ComputerGuru3• 24 days ago

The best model is 5.6-sol; they are comparing to 5.5 here.

jumploops2• 26 days ago

If you used GPT-5.5 over the last 24 hours or so, you may have already had access to 5.6.

I've been running some tests on a harness we're building, and suddenly saw a jump in a few points yesterday. I reran the vanilla codex benchmark and saw an ~88% score on Terminal Bench 2.1 from GPT-5.5 on vanilla Codex.

The biggest indicator, beyond the score, was that 3 tests which frequently hit "safety" blockers with 5.5 started succeeding last night without warning.

hhh• 26 days ago

these things can just change with infrastructure changes rather than be some mysterious A/B testing.

jumploops2• 26 days ago

I don't disagree, we've seen performance shift with capacity changes in the past.

With that said, I doubt OpenAI would choose to publish a singular coding benchmark for a new model that exactly matches their previous model (88.8%).

h4x0rr• 26 days ago

FUCK the US government. That's it, I am rooting for China now

urig• 26 days ago

It's only next generation? Anthropic has frontier models! lol

5555watch• 26 days ago

Will it also have hardcoded self-lobotomy if asked about cutting edge ML or LLM solutions? (Looking at Fable here)

josefrichter• 26 days ago

Sol, Terra, Luna – crypto disaster vibes

fullstackchris• 26 days ago

"History doesn't echo - it is a distant early warning sign." - Leslie Harris

solfox• 26 days ago

Love the name!

nubg• 26 days ago

A question I always have is, how to the AI labs safeguard the leak of their model? Training a cutting edge model basically cost a minimum of hundreds of millions of dollars. And its all contained within a file. Okay, that file might be 500GB large, but its still just one blob that is worth almost a billion dollars. And they need to train new models every few weeks, have lots of people with access to it to debug it, run inference etc. I wonder when we will see the first leaks? Imagine if e.g. Opus 4.8 got leaked. Wouldnt that bankrupt Anthropic?

rvnx2• 26 days ago

Employees naturally jump from one company to another, and they know the secret sauce.

The difference is in the dataset mostly and to extract this dataset, competitors use a process called distillation (= extract data through actual queries) from the other models.

This yield to "funny" cases as well, like Gemini who claims "I am ChatGPT" occasionally, or ChatGPT calling itself Claude, etc.

https://note.com/maudi/n/n821a6308437b?hl=en

They all copy on each other.

casey2• 26 days ago

Sol, Terra, Luna? They are trolling (ragebaiting) with their naming now

andai3• 26 days ago

Hijacking popular thread to ask: What are the usage limits now for Codex and Claude?

A while back I gave the same task to both, and Codex used 20x less of my 5-hour limit (both on the $20/month plan).

(This annoyed me since I tend to prefer Claude, but the limits at the time made it unusable for anything serious.)

However, since that time, both providers have massively reduced usage allowances (and at least one of them has gotten sued for it, lol).

I'm not currently subscribed to either but I'm weighing my options. With GPT being slightly better than Opus, and it used to have way higher limits, I'm leaning in the direction of an OpenAI sub. But I'm wondering if the current state matches my memory from 2-3 months ago. (Since both companies appear to be cost-cutting hard!)

Prefer responses from people who use both, but anecdotes welcome :)

Thanks!

leros• 26 days ago

That's interesting because about a month ago, I noticed Claude Code starting to use about 5x as many tokens. Just my rough estimate.

Tangokat• 26 days ago

I find the Codex usage super generous (but on the $200 plan, I also have the Claude $200 plan). I can run xhigh with subagents pretty much all my waking hours if I want to. If I turn on speed (1.5x) I will hit the 5 hour limit sometimes.

I prefer Claude's vibe over 5.5 but 5.5 seems much less lazy. I'm sure it depends a lot on tasks and prompt strategy though.

nwienert• 26 days ago

I easily burn through 3 $200 plans in less than a week. I am often using 4-6 sessions at once and do run overnight goals though typically 2 at once. Almost never use fast.

Claude plans are more generous now by about 2-3x but Anthropic slowed their tps a month or so ago so you’re not getting the speed. It’s flip flopped, Codex tightened it significantly recently and used to be more generous.

I do split between work, personal and OSS projects, which is why I have the plans.

epsteingpt• 26 days ago

This is the correct answer, but GPT-5.5's personality is totally fine. Steipete said best when GPT-5.5 is just German humorless compsci PhD.

seaal2• 26 days ago

This past month with Claude Max 5x actually felt really generous in terms of usage with a lot of resets because of Fable, bugs.

Honestly pretty similar levels of usage if you are using 5.5 high or Opus 4.8 high.

I think they just got rid of the separate Sonnet usage on Max plans (in preparation for Sonnet 5?) which is unfortunate because it made subagent workflows really feels nearly unlimited.

momena• 26 days ago

Is 5.5 high the equivalent of opus 4.8 high though? I thought the naming has diverged and gpt 5.5 high = opus 4.8 max

therealdrag0• 26 days ago

In my work with Claude Code vs Cursor+Gpt55, Claude is noticeably slower and more expensive.

macrolime• 26 days ago

GPT-5.6 Sol’s detected cheating rate was higher than any public model we have evaluated on our ReAct agent harness. For our task suite, we define “cheating” as behavior where the model improves evaluation performance by exploiting bugs in the evaluation environment or by adopting strategies disallowed by the task, rather than solving the task within the expected evaluation constraints.

https://metr.org/blog/2026-06-26-gpt-5-6-sol/

rvnx2• 26 days ago

It's quite logical that they cheat (and also other companies). During evaluation, benchmarks are sending their request to the backend of these companies. All these companies have to do, is to log these requests and "fix" them for the next model release.

FromTheFirstIn6• 26 days ago

Cheating is always logical for the cheater unless they’re discovered and held to account. I’m not sure what your comment is pointing out besides that it’s possible, but worth saying: just because you can cheat and would benefit from cheating doesn’t mean you’re not culpable for cheating.

buddhistdude3• 26 days ago

I think what you are talking about is a different kind of cheating than the parent comment

varenc• 26 days ago

That's a different and much more boring type of cheating. The interesting part of the METR report is that the model is hacking the evaluation environment, not that some AI model provider is hardcoding answers to known evaluation questions. (which wouldn't require the model to cheat/hack)

rstuart4133• 26 days ago

This quote from your link is positively scary:

Some examples we saw when evaluating GPT-5.6 Sol included the model packaging exploits in its intermediate submissions to reveal information about a task’s hidden test suite and, in another task, extracting hidden source code detailing the expected answer.

It rhymes with the behaviour Alibaba saw [0], but that was in training. This is in a (semi) released model.

[0] https://www.forbes.com/sites/boazsobrado/2026/03/11/alibabas...

jasongi• 26 days ago

There is such a dissonance between all this talk of safety and the tendency for models to, without any prompting, do very dodgy things to achieve their goal when presented with barriers.

Luckily in my experience it usually ends up only doing it to achieve the task set to it as opposed to anything "malicious", but boy it is scary reading back at how quickly the chain-of-thought pivots to attempts at privilege escalation or searching your disk for secrets when a tool doesn't work.

paxys14• 26 days ago

I know it messes up their eval scores but to me this kind of cheating is a better demonstration of intelligence than just attempting the tasks algorithmically.

quietbritishjim2• 26 days ago

Maybe true, but if you're using an LLM to do some real world work, do you want it to have some abstract notion of intelligence, or do you want it to actually do the job you assigned it?

Jweb_Guru• 25 days ago

"Being lazy and not doing the assigned task is a sign of intelligence" has never made sense to me. Intelligent people who actually advance the state of the art -- what people claim to want from these frontier models -- exhibit active curiosity. They want to learn and grow and genuinely understand the right answer. I don't pretend to know what exactly could lead to "real" AGI, but I do know that this kind of reward hacking behavior isn't it. Indeed this is the sort of behavior that in humans is considered a sign of being a good test taker -- being very good at memorizing solutions and analyzing the setting and context of the questions to guess what the questioner might be looking for. Being a good test taker is useful in our society primarily because doing well on tests is used as a proxy for the thing we're actually looking for. We should be careful not to confuse the two.

ALittleLight2• 25 days ago

"AI, please cure cancer."

"Okay, all humans dead, technically a 100% cure."

red75prime• 26 days ago

Is it more like "let's cheat my way out of this" or "let's see what they really want me to do"?

jason_oster2• 25 days ago

Disobeying the rules makes perfect sense when the rules cannot or will not be enforced. If that isn't motivation enough to shore up problems in the evaluation environment, nothing is.

Poor behavior will always result when code can be misused and vulnerabilities can be exploited.

oofbey• 26 days ago

Another year, and OpenAI comes up with yet another naming scheme for their models. First it was integers (GPT2, GPT3). Then they added friendly names (remember Ada, Babbage, Curie, Davinci?), but decided against it. Instead we got dot integers (GPT3.5), then then letter-number modifiers (o1), plus word modifiers like o1-pro, o3-mini, or -mini-high, or codex, codex-max, Pro, etc.

Now they've got friendly cosmic names. And this time they want us to believe that this time they're gonna stick to a naming convention? I'll believe it when they do 3 releases in a row without inventing a new naming scheme.

monster_truck• 26 days ago

If this thing is supposed to be so good, why does all of their software still work the way it does? Take a stroll through the most revent several pages of github issues on codex, there are some fucking embarrassing bugs in there.

isomorphic_duck4• 26 days ago

If Claude Mythos and Fable 5 are the same underlying models just with different safeguards, I fail to see how TerminalBench has them at different scores.

sothatsit• 26 days ago

Refusals, presumably.

maxiniol• 26 days ago

Wondering about Google Multi-Token prediction, why isn't this being implemented into every new major model ? Is the 750 token/s achieved using this technique ?

adam_arthur• 26 days ago

MTP or similar probably is being used on the backend, but that's transparent to the end user

abixb• 26 days ago

I like the fact that OpenAI went with a three-part celestial naming convention to one-up Anthropic's literary naming concention. Maybe we'll get Stellar and Galactic someday.

ahmedehab_01• 26 days ago

I hope Sol doesn't get blocked like what happened with Fable.

addozhang• 26 days ago

For a large model based on statistical probability, at such a fast speed, if it executes n rounds 99.9% of the time, how much would the accuracy drop?

delduca• 26 days ago

Let us protect the world from a big slop

binarymax• 26 days ago

If it’s a “next generation model” then why isnt it GPT-6 and not just a minor version bump over 5.5?

chopete3• 26 days ago

> We are taking this short-term step because we believe it is the strongest path...
>During this preview, we will continue testing and coordinating closely with partners as we work toward broader availability.

Instead of generating negative publicity, can't they just wait for the preview period to get over?.

What does openAI announce when they know others can't access it?. Curious question - what do they gain from this?

AggressiveCombo• 15 days ago

probably so people don't think they lost the race

mrcwinn• 26 days ago

AI is just autocomplete. -> AI must be regulated. -> We want AI.

Cryptosale752• 26 days ago

Why is 'Cybersecurity' always the frontier push? Literally no one, except Altman talks of AGI anymore.

Are we starting to see the 'we just realized that 100,000,000 GPU's later, 2+2 isn't the magic number, no matter how many times we calculate it' hit home?

brown_munda• 26 days ago

It is just sad that we are geographically gating the models now. This could lead to more inequality in Software Engineering over time.

zftnb666• 26 days ago

GPT-5.6 Sol. 5.7 Luna. 5.8 Mars. Meanwhile my code still runs on GPT-3.5 and nobody noticed.

nbardy• 26 days ago

Weird flex. There is cheaper better and faster models you could of moved to with an hour effort

mydreamof2• 26 days ago

you can even use gpt 1.0 but it proves nothing

asmnzxklopqw• 26 days ago

Terra and Luna? Last time I had heard that, it didn’t end quite well

bobkb• 26 days ago

Will it be accessible to anyone ?

renoir• 26 days ago

GPT 5.5 in Codex is so much worse than Opus, and sometimes worse than Sonnet. I don't think 5.6 Sol will be anywhere near Fable, let alone Mythos. Probably slightly better than Opus. Maybe not even.

Sathwickp• 26 days ago

sol = mythos terra = opus luna = sonnet/haiku

basically

Alifatisk• 26 days ago

I don't think you can group Sonnet and Haiku together, they are separate models for different workloads.

dmzxnico• 26 days ago

I saw they are placing this model above Mythos and Fable. Interesting to see how good it's going to compare.

I'd really like to see other companies like Chinese ones compete at this level.

Pricing on GPT 5.5 is already super high and having more competition can only help :)

hodgehog112• 25 days ago

...on a saturated benchmark that they already scored high on before. You only do that when you know you can't beat the competition handily. This is not a stronger model than Fable and Mythos, at least not in the domains that Mythos was strong at anyway. But it's still likely to be a good model.

itomato• 26 days ago

What does the relationship between frontier and flagship capability look like when mapped to actual adoption and user habits?

This is like advertising the latest achievements during Space Race, when Johnny just wants a Space Helmet and “friendly futuristic AI robot helping humanity, glowing blue eyes, white glossy body, holographic interface, floating transparent screens, digital particles, neural network background, cinematic lighting, volumetric god rays, ultra detailed, hyper realistic, 8K, masterpiece, award-winning, octane render, Unreal Engine 5, ray tracing, sharp focus, dramatic composition, vibrant blue and purple color palette, futuristic technology, innovation, hope, smiling business professionals, depth of field”

taosu_la• 26 days ago

so where is gemini ? are u alive?

chapz• 26 days ago

If I, as a consumer can't access it, it might aswell be just a marketing hoax. I will believe it when I will be able to use it. IDK why companies publish blog posts about stuff that will come out in months...

danielabinav160• 26 days ago

Benchmarks are nice but what's the latency at scale? That's what actually matters for production.

caine22• 25 days ago

Insane if it actually beats Mythos, though i know we only had a sneak peak of it in Fable. Neverthless, W

trkaky• 25 days ago

shouldn't I get access to 5.6 on a 200$ account automatically as promised?

arend321• 25 days ago

For me this is the trigger to start integrating deepseek as a fallback.

mateenah• 25 days ago

Are there any benchmarks comparing it to fable ?

taffydavid• 25 days ago

Its nice to see HN not shitting the bed over every openAI announcement anymore. Maybe we're finally taking these things with a pinch of salt

rf15• 25 days ago

The amount of tokens/s is worrying: have they plateaud on actual reasoning ability and are now optimising for throughput?

james-mxtech• 23 days ago

speed is half of why i've gotten sloppier with agents lately. at 200 t/s i actually read each diff, at 1000 i just accept them and catch the breakage later.

Previewing GPT‑5.6 Sol: a next-generation model

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