Earlier quoted context omitted.
If you’re still calling it slop at this point you have an axe to grind.
Do you use LLMs for anything but code?
I do, a lot of things, it’s extremely useful.
Previewing GPT‑5.6 Sol: a next-generation model
621–630 of 797 posts
Re: Previewing GPT‑5.6 Sol: a next-generation model
#622Earlier quoted context omitted.
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.
I really don't feel this way. Seemed pretty similar to me, noticeably better, but marginally. What am I missing?
Nothing. It had marginal gains. People just romanticize it cause it's gone.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#623Easily 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…
> 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.)
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.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#624GPT 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.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#625Earlier quoted context omitted.
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.
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.
Yes, I've just come to the end of implementing all the planning I did while Fable was available. And nothing now comes close to creating plans that could be coded and just worked like it did.
On a large C codebase, Claude hallucinates constantly, and GPT 5.5 gets there are with a lot of help, but still gets things wrong.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#626Easily 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…
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?
Re: Previewing GPT‑5.6 Sol: a next-generation model
#627Earlier quoted context omitted.
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".
The government doesn't have a Department of Vector Pelicans?
No, but Ministry of Silly Prompts is not out of question.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#628Here 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…
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...
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.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#629Easily 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…
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"
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.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#630I 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…
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?
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