GPT-5.6

Post by gershy » Thu, Jul 09, 2026, 7:37 PM UTC

postalcoder wrote: post #114

minimaxir wrote: post #26

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…

> Avoid generic brevity instructions: GPT-5.6 is more sensitive than GPT-5.5 to instructions such as “Be concise,” “Keep it short,” or “Use minimal text.” RIP Caveman skill. Six month good. Now skill dead.

Post by froh » Thu, Jul 09, 2026, 7:38 PM UTC

bevekspldnw wrote: post #331

10xDev wrote: post #234

Earlier quoted context omitted.

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.

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.

Post by frostterra » Thu, Jul 09, 2026, 7:39 PM UTC

wwind123 wrote: post #306

_superposition_ wrote: post #222

Earlier quoted context omitted.

I've been using codex app server. Works great. https://learn.chatgpt.com/docs/app-server

Hmm, thanks. Didn't know about this. But looks like a bunch of hassle to set it up?

Post by hk__2 » Thu, Jul 09, 2026, 7:40 PM UTC

ljm wrote: post #208

hk__2 wrote: 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.

Post by astrange » Thu, Jul 09, 2026, 7:41 PM UTC

aappleby wrote: post #429

simonw wrote: 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

Surely "how to draw a SVG pelican on a bike" has made it into the training data by now ...