With Codex (5.3), the framing is an interactive collaborator: you steer it mid-execution, stay in the loop, course-correct as it works.

With Opus 4.6, the emphasis is the opposite: a more autonomous, agentic, thoughtful system that plans deeply, runs longer, and asks less of the human.

that feels like a reflection of a real split in how people think llm-based coding should work...

some want tight human-in-the-loop control and others want to delegate whole chunks of work and review the result

Interested to see if we eventually see models optimize for those two philosophies and 3rd, 4th, 5th philosophies that will emerge in the coming years.

Maybe it will be less about benchmarks and more about different ideas of what working-with-ai means

The new Opus 4.6 scores 65.4 on Terminal-Bench 2.0, up from 64.7 from GPT-5.2-codex.

GPT-5.3-codex scores 77.3.

> GPT‑5.3‑Codex is our first model that was instrumental in creating itself. The Codex team used early versions to debug its own training

I'm happy to see the Codex team moving to this kind of dogfooding. I think this was critical for Claude Code to achieve its momentum.

While I love Codex and believe it's amazing tool, I believe their preparedness framework is out of date. As it is more and more capable of vibe coding complex apps, it's getting clear that the main security issues will come up by having more and more security critical software vibe coded.

It's great to look at systems written by humans and how well Codex can be used against software written by humans, but it's getting more important to measure the opposite: how well humans (or their own software) are able to infiltrate complex systems written mostly by Codex, and get better on that scale.

In simpler terms: Codex should write secure software by default.

I know that's anecdotal, but it just seems Claude is often the default.

I'm sure there are key differences in how they handle coding tasks and maybe Claude is even a little better in some areas.

However, the note I see the most from Claude users is running out of usage.

Coding differences aside, this would be the biggest factor for me using one over the other. After several months on Codex's $20/mo. plan (and some pretty significant usage days), I have only come close to my usage limit once (never fully exceeded it).

That (at least to me) seems to be a much bigger deal than coding nuances.

  | Name                | Score |
  |---------------------|-------|
  | OpenAI Codex 5.3    | 77.3  |
  | Anthropic Opus 4.6  | 65.4  |

I wish they would share the full conversation, token counts and more. I'd like to have a better sense of how they normalize these comparisons across version. Is this a 3-prompt 10m token game? a 30-prompt 100m token game? Are both models using similar prompts/token counts?

I vibe coded a small factorio web clone [1] that got pretty far using the models from last summer. I'd love to compare against this.

[1] https://factory-gpt.vercel.app/

Can you guys point me ton a single useful, majority LLM-written, preferably reliable, program that solves a non-trivial problem that hasn't been solved before a bunch of times in publicly available code?

Interesting

they forgot to add “Can’t wait to see what you do with it”

This is hilarious lol

GPT-5.3-Codex dominates terminal coding with a roughly 12% lead (Terminal-Bench 2.0), while Opus 4.6 retains the edge in general computer use by 8% (OSWorld).

Anyone knows the difference between OSWorld vs OSWorld Verified?

Am I better off buying 1 month of Codex, Claude, or Antigravity?

I want to have the agent continuesly recompile and fix compile errors on loop until all the bugs from switching to f32 are gone.

Anyone know if it is possible to use this model with opencode with the plus subscription?

This week, I'm all local though, playing with opencode and running qwen3 coder next on my little spark machine. With the way these local models are progressing, I might move all my llm work locally.

> We are working to safely enable API access soon.

May I at least understand what it has "written". AI help is good but don't replace real programmers completely. I'm enough copy pasting code i don't understand. What if one day AI will fall down and there will be no real programmers to write the software. AI for help is good but I don't want AI to write whole files into my project. Then something may broke and I won't know what's broken. I've experienced it many times already. Told the AI to write something for me. The code was not working at all. It was compiling normally but the program was bugged. Or when I was making some bigger project with ChatGPT only, it was mostly working but after a longer time when I was promting more and more things, everything got broken.

I really do wonder whats the chain here. Did Sam see the Opus announcement and DM someone a minute later?

Seems to be slower/thinks longer.

https://gist.github.com/simonw/a6806ce41b4c721e240a4548ecdbe...

Also, there is no reason for OpenAI and Anthropic to be trying to one-up each other's releases on the same day. It is hell for the reader.