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Previewing GPT‑5.6 Sol: a next-generation model

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Re: Previewing GPT‑5.6 Sol: a next-generation model

#201

Post by Gingersnap123 »

tontinton wrote: post #186
gandreani wrote: post #177

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 vers…

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)

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Re: Previewing GPT‑5.6 Sol: a next-generation model

#203

Post by hereme888 »

HarHarVeryFunny wrote: post #149
jdw64 wrote: post #44

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 averag…

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.

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.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#204

Post by micimize »

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).

Re: Previewing GPT‑5.6 Sol: a next-generation model

#205

Post by mlyle »

helloplanets wrote: post #184
gandreani wrote: post #177

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 vers…

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-...

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.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#206

Post by dgellow »

paxys wrote: post #59
wolttam wrote: post #56

Earlier quoted context omitted.

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...

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

There is actual market competition to host open models. If one provider stops offering a model you likely can find another provider that will

Re: Previewing GPT‑5.6 Sol: a next-generation model

#208

Post by hereme888 »

jdw64 wrote: post #137
pawelduda wrote: post #90

Earlier quoted context omitted.

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

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 b…

What do you think of modern open-source codebases presently available to the public? Is closed-source/proprietary code that much better?

Re: Previewing GPT‑5.6 Sol: a next-generation model

#210

Post by mchusma »

HyperL0gi wrote: post #29

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…

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.

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