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GPT-5.6

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Re: GPT-5.6

#581
post #478

Earlier quoted context omitted.

Information density of the prompt is the most important factor in my experience. And interestingly, LLMs seem particularly bad at writing prompts for other LLMs for this reason (you can guide them to be more dense, just speaking by default). Conciseness is usually a byproduct of information density though.

Lexical-priming->semantic-space-constraint;specialized-lexis+=sharp distributional-signature;∴ tight concept-cluster; generic-lexis->diffuse-activation, broad candidate-set;Attention-heads key/query-match domain-tokens;"Hamiltonian"->{operator,eigenstate,quantum,energy}->register+domain locked;Net:constrained-decoding,vocab=soft-prior over output-distribution; register-matching;#taskdef=decompress->continue

Chatbot expanded this into something that made sense, but I've no idea if it's what you meant. There's an irony there somewhere.

Re: GPT-5.6

#582
post #489
post #379

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

this looks like the same shit from 4 years ago. give it up.

The first time I did this was actually less than two years ago - in October 2024 - and it's fun seeing how much better they've got since then: https://simonwillison.net/2024/Oct/25/pelicans-on-a-bicycle/

Re: GPT-5.6

#583
post #208
post #142

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.

Purely anecdotally the one persistent issue I have with LLMs writing code is that they are absolutely paranoid and add a load of indirection and defensive crap and even if you prompt to avoid that it will often require manual steering to remove the cruft.

Fallbacks and backward compatibility are killing me :) So many code paths that just don't fail predictably.

Re: GPT-5.6

#584
post #520

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) ?

What destructive actions are you afraid of in particular? Honestly the models are pretty smart, I let the agents go --yolo and nothing bad has ever happened (yet) that couldn't be solved with git.

I'm not concerned about the code it's working on, but rather anything else - modifying files outside of the project dir (e.g. incorrect tool call), modifying system configuration, doing something bad on the internet, etc.

Re: GPT-5.6

#585

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) ?

Don't let it outside the sandbox. Don't let it have access to anything but dev environments. Continue using git. Never had any issues.

Which agent/sandbox are you referring to?

Re: GPT-5.6

#586

"We've extended usage of Claude Fable" message incoming any day now.

Or an allegedly even more dangerous model that they refuse to release. What a joke Anthropic has become.

Re: GPT-5.6

#587
post #38

Funny to see that they did not include Fable 5 in their GeneBench and LifeSciBench comparisons because "it does not answer advanced biology questions and refuses the majority of questions in this eval". Winner by default!

Well it seems like they removed quite a few 3rd party benchmarks they used for GPT-5.5 release where Opus 4.7 was better and added many new benchmarks created by them where conviniently GPT leads.

Seems a bit more hand picked than usual to me..

Re: GPT-5.6

#588
post #503

Based on the Intelligence vs. Cost graph, not clear to me why anyone would use Terra? Luna looks quite interesting though, happy to see OpenAI still serving the more budget-oriented side of the market (seems like Anthropic and Google have lost interest there). https://artificialanalysis.ai/articles/gpt-5-6-has-landed

Cost and intelligence aren't the only axes. Terra has better latency and output speed than Sol for example.

Re: GPT-5.6

#589

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?

Mythos doesn't appear to be on the verified leaderboard for ARC-AGI 3

Re: GPT-5.6

#590

Earlier quoted context omitted.

These aren’t raw base models they are the result of a ton of RLHF and various adjustments. Bitter lesson wildly overstated in this context.

More RLHF is in fact scaling.

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