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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

#421

Post by DonHopkins »

donquichotte wrote: post #286
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…

> 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.

Now start thinking, if possible.

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

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

#422

Post by devmor »

vb-8448 wrote: post #239
devmor wrote: post #212

Earlier quoted context omitted.

“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 yo…

> how many other people have encountered a problem close enough to yours and solved it somewhere on the open internet I'm 100% sure that all our web, cc, codex or whatsoever sessions are used in the training, RL or either both. This makes the size of the universe models know about at least one order of magnitude bigger than the open internet.

I think you have misused the term "order of magnitude" or just don't grasp the scale of the internet.

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

#423

Post by Tangokat »

andai wrote: post #417

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 th…

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.

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

#424

Post by b112 »

kevindamm wrote: post #416
b112 wrote: post #388

Earlier quoted context omitted.

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, analyticall…

Why remove the code and binary artifacts, though? Don't you want to verify that the business logic is accurate and the processing is deterministic? In some circumstances there is no substitute for something that you know will produce the same answer for a given input, consistently. And that's before even considering the watts per response.

The AI is the business logic, and the processing, and all of it. The context window is effectively infinite, with layered context window depth and speed.

Think of short and long term memory, or think of RAM vs SWAP. Dip into swap to pull needed data into RAM context. SWAP can be anything storage related, including a symbolic database or a best-encoded set of priorities.

If a person knows 100 knots, but hasn't tied one in 23 years, they might have to think a bit before they get full use of their long term memory... and tie that knot. I don't see an issue with layered speed context, that is, GPU ram, slower RAM, DB storage, all in the same format.

Imagine a world where a 'factory' is just high-tech 3d printing, with a dozen different methods (eg, plastic, laser+metal, etc), and getting specs for everything possible is, well, an immense amount of work. Imagine having a billion item catalog of things to print, and, imagine new requests for new things to print.

And the request doesn't come from an expert, but from some dude who sketched something on the back of a cardboard box.

The LLM can pull from long term storage for how those things were done before, how similar things were done before, and just get to work.

Regardless, the connection was what I was talking about before. Data transfer. Do you need http? json once established? What? Imagine instead that's all in the wind?

And it's so fast, so capable, that dynamic is easy.

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

#425

Post by _se »

adamtaylor_13 wrote: post #344
fatata123 wrote: post #237

Earlier quoted context omitted.

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.

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.

Everyone saying it is in the "not as good as they think they are" camp is the very obvious explanation.

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

#426

Post by windexh8er »

Kirby64 wrote: post #347
windexh8er wrote: post #320

Earlier quoted context omitted.

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/

It’s not just old, it’s also tiny and quantized. It’s llama 3.1 8b at 3/6-bit quant. This is the type of thing you can run on almost any device…

I get that, but not at 15k tokens/s.

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

#427

Post by seaal »

andai wrote: post #417

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 th…

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.

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

#428

Post by hssa45 »

vatsachak wrote: post #317
esafak wrote: post #296

Earlier quoted context omitted.

> - their internal representations are disgusting compared to JEPA You say this based on a theoretical understanding or did you inspect them?

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

Sounds interesting, any links?

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

#429

Post by Kirby64 »

windexh8er wrote: post #426
Kirby64 wrote: post #347

Earlier quoted context omitted.

It’s not just old, it’s also tiny and quantized. It’s llama 3.1 8b at 3/6-bit quant. This is the type of thing you can run on almost any device…

I get that, but not at 15k tokens/s.

But it’s irrelevant. 750 tokens/s on a full frontier model is useful. 15000 poor quality tokens is much less useful no matter how much scaffolding you put around it.

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

#430

Post by anon7725 »

markrages wrote: post #372
rasengan wrote: post #363

Earlier quoted context omitted.

To be fair, whenever I join a pre-existing code-base [1], it's the same. I have no idea and have to map it out ;) [1] Not AI codebases (and of course, AI code bases I guess)

I can't be the only one whose memory is so bad that I am like this in my own code base.

In your own codebase you can at least run a "you simulator" to arrive at the answer fairly reliably. "Where would I have put this bit? Oh yes, of course ..."
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