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"GPT‑5.4 interprets screenshots of a browser interface and interacts with UI elements through coordinate-based clicking to send emails and schedule a calendar event."

They show an example of 5.4 clicking around in Gmail to send an email.

I still think this is the wrong interface to be interacting with the internet. Why not use Gmail APIs? No need to do any screenshot interpretation or coordinate-based clicking.

The 'AI' endgame is a robot that sits in your seat and does all of your tasks.
The marquee feature is obviously the 1M context window, compared to the ~200k other models support with maybe an extra cost for generations beyond >200k tokens. Per the pricing page, there is no additional cost for tokens beyond 200k: https://openai.com/api/pricing/

Also per pricing, GPT-5.4 ($2.50/M input, $15/M output) is much cheaper than Opus 4.6 ($5/M input, $25/M output) and Opus has a penalty for its beta >200k context window.

I am skeptical whether the 1M context window will provide material gains as current Codex/Opus show weaknesses as its context window is mostly full, but we'll see.

Per updated docs (https://developers.openai.com/api/docs/guides/latest-model), it supercedes GPT-5.3-Codex, which is an interesting move.

Grok has a 2M context window for most of their models.

For example their latest model `grok-4-1-fast-reasoning`:

- Context window: 2M

- Rate limits: 4M tokens per minute, 480 requests per minute

- Pricing: $0.20/M input $0.50/M output

Grok is not as good in coding as Claude for example. But for researching stuff it is incredible. While they have a model for coding now, did not try that one out yet.

https://docs.x.ai/developers/models

imo , the main feature is /fast ... who use 1M context and for what? the model become dumber already at 200K.. it's better to manage the context , and since 5.3, codex is very good at managing it
Based on my experience with LLMs the larger your input context the bigger the chance of something going sideways in the response. Not sure how to address this properly.
I’m sure the military and security services will enjoy it.
1 million tokens is great until you notice the long context scores fall off a cliff past 256K and the rest is basically vibes and auto compacting.
It's the same now with Gemini as well. Unfortunately. :(
Notably 75% on os world surpassing humans at 72%... (How well models use operating systems)
Bit concerning that we see in some cases significantly worse results when enabling thinking. Especially for Math, but also in the browser agent benchmark.

Not sure if this is more concerning for the test time compute paradigm or the underlying model itself.

Maybe I'm misunderstanding something though? I'm assuming 5.4 and 5.4 Thinking are the same underlying model and that's not just marketing.

can anyone compare the $200/mo codex usage limits with the $200/mo claude usage limits? It’s extremely difficult to get a feel for whether switching between the two is going to result in hitting limits more or less often, and it’s difficult to find discussion online about this.

In practice, if I buy $200/mo codex, can I basically run 3 codex instances simultaneously in tmux, like I can with claude code pro max, all day every day, without hitting limits?

It's interesting that they charge more for the > 200k token window, but the benchmark score seems to go down significantly past that. That's judging from the Long Context benchmark score they posted, but perhaps I'm misunderstanding what that implies.
Does this improve Tomahawk Missile accuracy?
Remember when everyone was predicting that GPT-5 would take over the planet?
$30/M Input and $180/M Output Tokens is nuts. Ridiculous expensive for not that great bump on intelligence when compared to other models.
Benchmarks barely improved it seems
I use ChatGPT primarily for health related prompts. Looking at bloodwork, playing doctor for diagnosing minor aches/pains from weightlifting, etc.

Interesting, the "Health" category seems to report worse performance compared to 5.2.

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> Steerability: Similarly to how Codex outlines its approach when it starts working, GPT‑5.4 Thinking in ChatGPT will now outline its work with a preamble for longer, more complex queries. You can also add instructions or adjust its direction mid-response.

This was definitely missing before, and a frustrating difference when switching between ChatGPT and Codex. Great addition.