Cerebras and OpenAI unveil GPT-5.6 Sol Ultrafast, delivering 750 tokens per second
Accelerating GPT-5.6 Sol Ultrafast
Cerebras and OpenAI have introduced Ultrafast Mode, a new service tier in the OpenAI API powered by Cerebras' Wafer-Scale Engine. It runs GPT-5.6 Sol at up to 750 output tokens per second without quality loss, making it 11x faster than Fable 5 and 5x faster than Opus 4.8 on Fast mode. In tests on Humanity's Last Exam, Ultrafast completed all 2,500 questions in 11 hours versus 78 hours for Claude Fable 5, and on GDP-Val it achieved a 5.6x end-to-end speedup. The service is now in limited preview.
Whereas formerly I might have to wait a couple minutes for a task to finish, it now finishes for me before I even have the opportunity to context-switch.
- iamcoder18
I've been waiting so long for something amazing to come out of the OpenAI and Cerebras collaboration.
> In our evaluations, GPT-5.6 Sol on Ultrafast mode answered all 2,500 HLE questions in 11 hours and 11 minutes. Claude Fable 5 needed 78 hours and 27 minutes, more than three days of continuous compute, to arrive at the same conclusions. In other words, Ultrafast worked through the frontier of human knowledge in a single working day, achieving comparable accuracy nearly 7× faster.
This is actually insane.
Hopefully the release ultrafast of Terra and Luna too.
- csallen
People underestimate the importance of speed on quality of thought, because people underestimate just how much quality is a result of simple iteration.
When an LLM thinks, it typically just makes one pass. It outputs tokens from top to bottom, beginning to end, and then it's done. But when people think, especially strong thinkers, we typically iterate and revise our thoughts on the fly. We do numerous passes. We stop and restart, we reconsider, we review, we reevaluate. Sometimes we do this so quickly and automatically that we don't even realize we're doing it. I think a lot of what separates a highly intelligent or effective person from others has less to do with the quality of their first pass and more to do with just how many additional passes they're able to do in the same amount of time, and of course what kind of criteria they're habituated to consider during their review passes.
Introspecting about this is difficult, but experimenting with LLMs is easy. First, simply ask an LLM to do something complex. For example, to come up with a new business idea, or to plan the next month of your life, etc. After it finishes, tell it:
"Review what you just wrote, according to some appropriate list of evaluation criteria that you come up with first. And then, based on the results, iterate and generate a better response if warranted."
It's insane how much better the next answer will usually to be. Often it'll catch and erase tons of hallucinations, logical errors, and inefficiencies […]
- Topfi
Unless I have read over it, besides the animation in the intelligence vs speed graph which only mentions internal data and not whether they truly reran the AA suite, there is no actually solid statement on the important aspect of performance.
Neither the Cerebras or OpenAI post [0] outright state that this performs exactly the same as regular 5.6 Sol. I feel if this was 1:1 just Sol but much faster, they'd (rightfully) scream that off the rooftops. A line such as "this is the same performance, just faster, with no downsides" would go a long way in clarity and communication. Along with no pricing information, I'll hold out on further information.
- GodelNumbering
The corresponding OpenAI post https://openai.com/index/previewing-ultrafast/
There is no pricing info, which could mean it's "if you have to ask..." territory or they are simply gauging interest before deciding
- wxw
> Compared with output speeds reported by Artificial Analysis GPT-5.6 Sol on Ultrafast mode runs 11x faster than Fable 5, and 5x faster than Opus 4.8 on Fast mode.
Awesome work. I'm personally very excited for faster models/inference.
I think speed is underrated to some degree in the current conversation. For a while, I was using Cursor's Composer quite a lot, even over frontier models, just because of how darn fast it was.
- ricardobeat
The omission of Mimo v2.5-Pro Ultraspeed, released in June, which can achieve 1000tok/s is an interesting flaw in the comparison graphs.
It is a bit outdated (scores ± 40% lower), but smart enough for a lot of coding tasks, and can cost under 1/10th of Sol.
- johnfn
This does look pretty incredible, but don't forget that incredible token thoroughput can only necessarily solve certain bottlenecks. If your e2e tests take an hour, they'll still take an hour after Ultracode. If the agent runs a 10 minute typecheck after a change, that will still take 10 minutes. grep over a massive codebase is still just as slow, etc. I say this not to take away from this accomplishment but just to ensure everyone here keeps a clear head about what it means - 14x faster tokens does not mean it completes every task 14x faster.
I suspect Humanity's Last Exam is without tool-calls, making it kind of the perfect benchmark to highlight how fast Ultrafast is, but not really the same as the everyday work you or I do.
- exabrial
Right now, the "economic model" of AI is "who has the best model", or really weights.
That'll go away eventually, just like operating systems eventually became free.
Instead, it's going to come down to selling inference hardware. We'll likely see the "apple" model where a custom OS runs on their hardware, but we'll probably also see more things like Cerebras become commodity hardware instead of kilowatt-class datacenter only hardware.