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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

#731

Post by imadierich »

dannersy wrote: post #666
lnrd wrote: post #470

Earlier quoted context omitted.

> 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.

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 ma…

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

#732

Post by imadierich »

dannersy wrote: post #725
frumiousirc wrote: post #680

Earlier quoted context omitted.

This split in what different people or groups get out of LLMs is pervasive and really interesting. In the beginning I was dismissive of those with bad experience with a "you are holding the tool wrong" smugness. But as I read more and more experience, I see all combos and I now know my initial knee jerk conclusion was clearly wrong. There are newbie programmers getting good or bad results as well as experienced devel…

I have seen plenty of greenfield projects go okay at first but never go the distance. These were mostly product software cases, where they were able to get something very professional looking very fast but AI ultimately always miss the mark because they are taking the median of what exists and not the specific needs of the customer they're developing for. So they get a ton of features and few that were necessary, the…

[dead]

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

#733

Post by jephs »

alansaber wrote: post #148
derwiki wrote: post #136

Earlier quoted context omitted.

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

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

The name was given to the project when it was supposed to be a demo for nerds, not a product. They accidentally a product, and woe! Too late, the name was stuck and wouldn't come off, even if you scraped at it with your fingernail a bit.

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

#734

Post by refulgentis »

cactusplant7374 wrote: post #721
mlrtime wrote: post #693

Earlier quoted context omitted.

First post?

The user has many comments and updoots if you look at their profile.

We’re being silly and spamming Slashdot spam comments :p (“imagine a Beowulf cluster” and “first post?”)

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

#735

Post by famouswaffles »

HarHarVeryFunny wrote: post #328
artursapek wrote: post #163

Earlier quoted context omitted.

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

My guess is that it's same base model as 5.5, but with additional post-training to improve and benchmaxx on a few things like that. If they really thought it was competitive with Mythos/Fable across the board, then why wouldn't they release a broader set of benchmarks, and why price it day 1 at 1/2 the cost of Fable?

>and why price it day 1 at 1/2 the cost of Fable?

Why would they price it the same as Fable it it doesn't cost the same as Fable ?

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

#736

Post by addaon »

refulgentis wrote: post #734
cactusplant7374 wrote: post #721

Earlier quoted context omitted.

The user has many comments and updoots if you look at their profile.

We’re being silly and spamming Slashdot spam comments :p (“imagine a Beowulf cluster” and “first post?”)

Me too!

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

#737

Post by aurareturn »

eli wrote: post #240
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'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 sm…

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.

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

#738

Post by razemio »

rubicon33 wrote: post #729
wolttam wrote: post #709

Earlier quoted context omitted.

I self-host Flash actually, but yeah. When I use their API I use it knowing that they probably train on the data, and knowing that it's probably used to improve future iterations of their models. But I use their API extremely rarely lately, because local Flash is good enough for me the vast majority of the time

And you’ve opened wireshark and verified the model is sending absolutely nothing? Not caching and sending later, etc?

Not sure if you mean something else, but the model itself is not able to send anything.

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

#739

Post by adrian_b »

rubicon33 wrote: post #729
wolttam wrote: post #709

Earlier quoted context omitted.

I self-host Flash actually, but yeah. When I use their API I use it knowing that they probably train on the data, and knowing that it's probably used to improve future iterations of their models. But I use their API extremely rarely lately, because local Flash is good enough for me the vast majority of the time

And you’ve opened wireshark and verified the model is sending absolutely nothing? Not caching and sending later, etc?

If you self host then you can audit the open-source llama.cpp or whichever other program you are using for inference, to see exactly what it does, and also whichever open-source harness you use for implementing a coding assistant or other agentic workflow.

The model consists of a bunch of data files, it does absolutely nothing by itself.

If you run inference on your own hardware, you have absolute control on how the LLM is used, not like when you use an external service provider.

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

#740

Post by Jweb_Guru »

paxys wrote: post #516
macrolime wrote: post #448

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/2026-06-2…

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.

"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.
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