BEGIN TRAN;

-- put the query here

commit;

I feel like I haven’t had to prod a model to actually do what I told it to in awhile so that was a shock. I guess that it does use fewer tokens that way, just annoying when I’m paying for the “cutting edge” model to have it be lazy on me like that.

This is in Cursor the model popped up and so I tried it out from the model selector.

I know it's only on a single benchmark, but I dont understand how it can be so bad...

Input: $5/M tokens at <=272K, $10/M tokens above 272K.

Output: $30/M tokens at <=272K, $45/M tokens above 272K.

Cache read: $0.50/M tokens at <=272K, $1/M tokens above 272K.

Significantly more expensive than Opus 4.7 beyond 272K and at least in my tasks, I haven't seen the model that much more token efficient, certainly not to such a degree that it'd compensate this difference. GPT-5.4 had a solid context window at 400k with reliable compaction, both appear somewhat regressed, though still to early to truly say whether compaction is less reliable. Also, I have found frontend output to still skew towards that one very distinct, easily noticeable, card laden, bluesy hue overindulged template that made me skeptical of Horizon Alpha/Beta pre GPT-5s release. Ended up doing amazing at the time for task adherence, which made it very useful for me outside that one major deficit. The fact that GPT-5.5 is still so restricted in that area is weird considering it's supposed to be an entirely new foundation.

Live decision and heavier agentic evals will continue being uploaded for 24 hours but I don't expect its leaderboard position to change at this point.

GPT 5.5 is the most intelligent public model. And significantly faster than its predecessor.

>API deployments require different safeguards and we are working closely with partners and customers on the safety and security requirements for serving it at scale.

And now this. I guess one day counts as "very soon." But I wonder what that meant for these safeguards and security requirements.

There is too much and there are too many, and some of their takes don’t fly if you use Claude daily.

Cheaper and slower than Opus.

   Knowledge cutoff: 2024-06
   Current date: 2026-04-24

   You are an AI assistant accessed via an API.

They all roughly produce junior developer-level code, continue to have mental breakdowns in their “thinking” stage, occasionally hallucinate things, delete pieces of code/docs they don’t understand or don’t like, use 1.5 times the necessary words to explain things when generating docs and so on.

I'm now testing "avoid sycophancy, keep details short and focus on the facts" in my AGENTS.md files.

All the AI players definitely seem to be trying to claw more money out of their users at the moment.

    $ uvx swival --provider chatgpt --model gpt-5.5

    APIError: ChatgptException

Gave it two very long-running problems I haven't had the courage to work on in the last 2.5 years, solved each within an hour.

- An incremental streaming JSON decoder that can optionally take a list of keys to stop decoding after. 1800 LOC about 30 minutes later, and now my local-first apps first sync time is 0.8s instead of 75s when there's 1.5 GB of data locally.

- Flutter Web can compile to WASM and then render via Skia WASM. I've been getting odd crashes during rapid animation for months. In an hour, it got Skia WASM checked out, building locally, a Flutter test script, and root caused the issue to text shadows and font glyphs (technically, not solved yet, I want to get to the point we have Skia / Flutter patch(es))

If you told me a week ago that an LLM could do either of these, without heavy guidance, I'd be stunned. And I regularly push them to limits, ex. one of Opus' last projects was a tolerant JSON decoder, and it ended up being 8% faster than the one built-in to Dart/Flutter, which has plenty of love and attention. (we're cheating a little, that's why it's faster. TL;DR: LLMs will emit control characters in JSON and that's fine for me, treating them as fine means file edit error rates go from ~2% to 0%)

I just wish it was cheaper, but, don't we all...

Either Opus 4.7 miscounts reasoning tokens, or it's A LOT more efficient than GPT 5.5

I thought they made GPT 5.5 more token efficient than 5.4, but it uses 2x the reasoning tokens.

[0]: https://aibenchy.com/compare/openai-gpt-5-5-medium/openai-gp...

In my place for example, a lot of doctors are using ChatGPT both to search diagnosis and communicate with non-English speaking patients.

Even yourself, when you want to learn about one disease, about some real-world threats, some statistics, self-defense techniques, etc.

Otherwise it's like blocking Wikipedia for the reason that using that knowledge you can do harmful stuff or read things that may change your mind.

Freedom to read about things is good.