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GPT-5.6

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Re: GPT-5.6

#621

Post by mhjkl »

docjay wrote: post #478
adam_arthur wrote: post #267

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

How do you make these compressed prompts like that

Re: GPT-5.6

#622

Post by sebastiennight »

derefr wrote: post #303
anticorporate wrote: post #141

Earlier quoted context omitted.

It seems like the way brevity instructions have changed is mis-aligned with how most people would expect to use them or are currently using them. Here's the example they give: > Instead of asking for the shortest possible answer, replace brevity instructions with prioritization: > Lead with the conclusion. Include the evidence needed to support it, any material caveat, and the next action. Omit secondary detail and r…

> Lead with conclusion. I would presume (perhaps falsely?) that an instruction like this would lead to the model presenting a conclusion not supported by the evidence, and potentially backtracking as it then tries to justify said conclusion. Yes, if deliberation happens, the model should figure out what it wants to say during that phase; but if you're using auto mode, the model is not going to be doing any deliberati…

You are absolutely correct. The second suboptimal part of the prompt is this:

> Trim introductions, repetition, generic reassurance, and optional background first.

It's not possible for the model to "trim" those before they've been output, so this is akin to telling it "not think of an elephant or even take the existence of elephants into consideration while solving this problem".

Re: GPT-5.6

#623

Post by newtwilly »

Jcampuzano2 wrote: post #152

I really wish there was just an easy guide on when to use Sol vs Terra vs Luna, and it just moves further into confusing territory when it comes to naming. The naming convention is especially difficult to decipher depending on what your native language is. Of course a latin language speaker might be able to easily determine oh yeah each one is slightly bigger than the other but I still think it borderlines too confus…

Use Luna. It's more performant than 5.5 and it's cheap. Hopefully it's cheap because it's more environmentally friendly than the bigger models. So you're doing a good thing. If it's a smaller model it may even be faster, but I haven't looked into it yet.

Re: GPT-5.6

#624

Post by matheusmoreira »

eig wrote: 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!

Anthropic just refuses to allow Fable to properly code review my projects. It's so obnoxious. If OpenAI's Fable equivalent is better at this, that'll get me to cancel my Anthropic subscription and switch.

Re: GPT-5.6

#625

Post by [deleted] »

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

[deleted]

Re: GPT-5.6

#626

Post by matheusmoreira »

midtake wrote: post #309
eig wrote: 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!

You shouldn't know too much about biology, stupid human. You might live your life in an unexploitable way.

Anthropic's talk of "uplifting" people was so abhorent.

Re: GPT-5.6

#627

Post by forshaper »

Syntaf wrote: post #6

Ok long time Claude Code user here; lately I've started to realize there's other great models out there I should be trying, but I'm hesitant to leave Claude Code behind for something new. What's the consensus today on codex vs claude code, does it really matter anymore?

Don't know about consensus, but I personally still find Opus to be better for sniffing codebase intent and checking things as a whole, while Codex seems more detail-oriented for individual files.

Re: GPT-5.6

#628

Post by ciefa »

gorgmah wrote: post #518

Anyone else noticed the "Extended: Fable 5 is included in your weekly limit through July 12 blablabla" disappeared from claude code? Did they panic-delete the july 12th deadline ?

I still see in the menu to select the model in the GUI (Claude Desktop, claude.ai etc).

Re: GPT-5.6

#629

Post by epolanski »

asadm wrote: post #183
Jcampuzano2 wrote: post #152

I really wish there was just an easy guide on when to use Sol vs Terra vs Luna, and it just moves further into confusing territory when it comes to naming. The naming convention is especially difficult to decipher depending on what your native language is. Of course a latin language speaker might be able to easily determine oh yeah each one is slightly bigger than the other but I still think it borderlines too confus…

it's simple: unless trivial TOIL, always use the highest at ultra max settings.

Non sense, and time consuming.

Re: GPT-5.6

#630

Post by zahlman »

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…

> ...tips for using the model:

> 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.”

I don't follow. Isn't "the model actually cares and will do what you say" a reason to use those kinds of instructions more liberally?

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