[flagged]
Previewing GPT‑5.6 Sol: a next-generation model
711–720 of 797 posts
Re: Previewing GPT‑5.6 Sol: a next-generation model
#712Earlier quoted context omitted.
That's literally the official FSF position. https://www.fsf.org/resources/hw > For example: the Free Software Foundation only purchases desktop machines which support Libreboot, and Thinkpad X200 and X60 laptops with Libreboot. All desktops and servers we buy are KGPE-D16 motherboards, which are supported by Libreboot. As a result, all of the workstations used by the FSF staff have a free BIOS. https://www.gnu.org/di…
Damn, that's awesome. I suddenly feel like replicating their setup and seeing how it goes.
For even more of a challenge, try replicating Richard Stallman's personal setup:
Re: Previewing GPT‑5.6 Sol: a next-generation model
#713Earlier quoted context omitted.
" I'd argue that current frontier models already exceed the abilities of average humans " for things that fit in their context window sure but LLMs can't learn over time the way humans can. One example is LLMs are very good at writing a few thousands line of code but they absolutely cannot write coherent million line codebases. By average human I meant the average skill level for the job. AGI would need to be able to…
Yeah it's not true that for every job, it is better than median worker of that job. But it is conceivable that for almost all jobs it is already better than the median human (not just workers of that job).
You have to understand that the median human is terrible at (almost) everything. Humans, the only examples of general intelligence we know, are economically valuable precisely because they can train themselves to specialise at a (relatively) narrow task over time. You don’t measure how good a coding model is by how well it programs relative to Doctors, or how well it can prove theorems relative to baristas, or how well it can write coherent novels relative to programmers. That would be a dumb metric.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#714Earlier quoted context omitted.
Your experience with DeepSeek v4 Flash differs from mine: while I usually use DeepSeek v4 Pro (that is also inexpensive), I find using DeepSeek v4 Flash with the Fireworks.ai API and properly configured OpenCode to be very good for routine work, and it is pleasantly very fast. Admittedly I use DeepSeek v4 Pro for difficult problems. I encourage people to at least once a month to do a quick evaluation with their own p…
We are also using fireworks as our model provider. Our harness is openClaw, so tasks are not only coding but all kinds of tasks. For instance, I asked to fetch some info from the web via Chrome browser and to collect the info in an MD. The MD never appeared, even though it claimed to. I asked it three times to write the MD and it was always: “oh yes, I do it now..” then nothing. The search itself also was very bad be…
Have to ask: did you try 'xhigh' thinking effort with Flash? I also found it nearly unusable on just 'high', but on 'xhigh' it's nearly equivalent to Pro's 'high'.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#715shouldn't I get access to 5.6 on a 200$ account automatically as promised?
Re: Previewing GPT‑5.6 Sol: a next-generation model
#716For me this is the trigger to start integrating deepseek as a fallback.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#717> 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. This is really exciting. I work on voice AI, and we're still using 4.1/4.1 mini since none of the frontier models come close on latency. I'm excited to be able to have more interactive experiences, I think it'll unlock new ways of working with these models.
Also building voice agents and have found GPT 5.4 with no thinking to be the sweet spot for latency vs intelligence vs cost. GPT 5.5 with no reasoning is actually slightly faster, and much smarter, but too expensive. What I'm really looking forward to are the next gen speech to speech models. gpt-realtime-2 is almost there, but not quite good enough for our use case. 5.4 actually beats it on answer latency even casca…
What is the latency you are seeing with 5.4 no reasoning? And where have you landed for stt and tts solutions?
Re: Previewing GPT‑5.6 Sol: a next-generation model
#718Earlier quoted context omitted.
" I'd argue that current frontier models already exceed the abilities of average humans " for things that fit in their context window sure but LLMs can't learn over time the way humans can. One example is LLMs are very good at writing a few thousands line of code but they absolutely cannot write coherent million line codebases. By average human I meant the average skill level for the job. AGI would need to be able to…
But in any case, I think more than 10% of information workers today can be replaced by current-generation models indefinitely.
It's decent at rote coding tasks, but I haven't seen these things be reliable enough outside of that specific task to make the claim that it can do the work of any information worker.
Re: Previewing GPT‑5.6 Sol: a next-generation model
#719Earlier quoted context omitted.
We still have the problem that auto regressive decoders are memory bound. The new Blackwell hardware combined with TensorRT-LLM and speculative decoding consistently can hit 1,000 TPS/user barrier, comparing to closer to ~250 TPS/user (out of 10k+/TPS on the server) Is there something I missed, this looks more like 14.4 to 56 on a 64kbps backing channel modem story. I have no doubt that there are still massive gains…
1000TPS - what model size?
Maverick 400B is what Nvidia used for their claim of 1k+ TPS on Blackwell GPUs.