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GPT-5.6 Sol sets a new SOTA on ARC-AGI-3: 7.8% Sol is the first verified frontier model to ever beat an ARC-AGI-3 game https://arcprize.org/results/openai-gpt-5-6
Seeing the dramatic differences in scores just going from high to xhigh is just another demonstration of the bitter lesson: Just keep scaling search and learning. We are probably going to need a lot more GPUs.
Earlier quoted context omitted.
I’d argue the opposite. I’ve switched back and forth from one to the other and Opus/Fable has been constantly better than any GPT in my daily work. It’s a bit slower but it does the things right, with as little code as possible, some comments where needed. Codex is faster but you always have to correct it because it got something wrong; it writes tons of code ("let me add a small helper") with obvious comments.
Sounds like you are talking past each other. GP is saying the harness of codex is higher quality, which I can believe, even if the models are not as good as Opus/Fable.
The developer's guide ( https://developers.openai.com/api/docs/guides/latest-model ) has some interesting semantic tips for using the model: > Intent understanding: GPT-5.6 can better infer the user’s underlying goal and intended level of work without you specifying every step. Continue to state important constraints, approval boundaries, and success criteria explicitly. > Original image detail: GPT-5.6 preserves the…
> Use shorter prompts: In internal evaluations, replacing long, explicit system prompts with minimal prompts improved scores by roughly 10–15%, while reducing total tokens by 41–66% and cost by 33–67%. A shorter prompt results in half as much tokens spend? I find this very hard to believe.
Should be relatively easy to test. And if it's true, just first use a very cheap near-SOTA model to first rewrite the prompt to a similar but shorter prompt before sending it to GPT-5.6.
pi.dev for example can control other harnesses.
An example: the other day for example I didn't understand why Claude Code CLI (which I hadn't used in a while) wouldn't let me cut/paste anymore (turns out they apparently fixed some long-standing scrolling and blinking SNAFU, but this modified how mouse selection/paste worked under Xorg but I didn't immediately realized they changed this)... I had to copy/paste the oauth challenge/response for I was logged out (maybe because I hadn't used Claude Code CLI in a while, dunno). But my usual copy/paste wasn't working and I didn't know how to fix it at first. And because I wasn't logged in, I couldn't use Claude Code itself for this.
My prompt was something like: "Screenshot the Claude Code TUI, transform the URL into a link, open that link in a broswer to get the oauth token, copy it character by character by simulating keypresses in the Claude Code CLI".
(remember: I had no idea how to paste with the mouse not with the keyboard, no I know but I was pissed off and wanted to be logged in immediately... So: another model / harness to the rescue).
(for the curious: it decided to use xdotool and use a 50 ms wait between simulated keypresses to copy the oauth token)
This worked just fine. And I that with a cheap model.
I think that just like Linux and Git owned many proprietary software, we'll soon have fully open-source harnesses orchestrating everything and delegating the work to proprietary tools (like "ChatGPT now Codex and vice-versa" and Claude Code)... If proprietary tools are even still needed at all.
Honestly I begin to wonder if they're even needed at all: the models, sure, while waiting for the open-weight ones to beat them. But those proprietary tools trying to lock people in?
I feel like the open source harnesses are already more powerful.
Here are 18 pelicans - six each for Luna, Terra and Sol at the six different reasoning effort levels (plus the price to generate each one): https://static.simonwillison.net/static/2026/gpt-5.6-pelican... Or if you want to see some in 3D, OpenAI featured a pelican riding a tricycle, bicycle, pony and another pelican in their livestream this morning: https://www.youtube.com/live/Wq45rvPGNHs?t=1070s
https://chatgpt.com/share/6a5009de-fff8-83ea-98ff-0da17d1d04...
GPT-5.6 Sol sets a new SOTA on ARC-AGI-3: 7.8% Sol is the first verified frontier model to ever beat an ARC-AGI-3 game https://arcprize.org/results/openai-gpt-5-6
Very interesting. My prediction is that Mythos would outperform Sol. Also what does this tell about Yann LeCuns whole world model theory? Bro has been going on and on about it. He has made multiple wrong predictions on the trajectory of LLMs. At some point his claim should be fully falsified no?
It's telling
I flip back and forth between whoever currently has the more powerful frontier model that isn't cost prohibitive - subscriptions only, API pricing a non-starter. Today that's Fable 5 which has been excellent, as soon as it's Sol I'll switch to that. The OAI/Anthropic harness behavior has mostly stabilized for me with consistent AGENTS.md that I sync with CLAUDE.md - I like pi (pi.dev) and have tried to build it up to…
Earlier quoted context omitted.
> We are probably going to need a lot more GPUs. Or a breakthrough in algorithms etc. The human brain, heck all bio brains, are proof that you don't need a lot of power or size for intelligence.
The human brain has 80 billion neurons and a 100 trillion synapses. I think you're underselling the processing power of that warm chunk of meat. The real message of the last 15 years has actually been the opposite: if you throw enough processing power at it, intelligence emerges.
Not specific to OpenAI / Codex, but I'm curious what people are doing to protect themselves from any destructive actions by their coding agents? Just install and pray? Explicity approve all actions? Reconfigure for safety? Run in a sandbox (Docker) ?
I live in fear lol. More seriously, I was blindly trusting the auto-classifier from claude code (same as the middle option when you do `/permissions` in codex), and it actually allowed the agent to do pretty hardcore `rm` and `git push --force-with-lease` commands, which I would have expected to have to approve manually. Luckily no major issue from those yet. The best option imo is the integrated cloud environments f…
Does it auto install all the dev/test tools it needs, maybe including things like web server & browser? Does your code live in the VM, or in some external repository? Is the lifetime of the VM the same as the agent, or does it persist until you remove it?
Where can I find documentation on this?