141–150 of 634 posts
I never really used Codex (found it to slow) just 5.2, which I going to be an excellent model for my work. This looks like another step up. 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.
Anthropic mostly had an advantage in speed. It feels like with a 25% increase in speed with Codex 5.3, they are now losing that advantage as well.
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Just some anecdata++ here but I found 5.2 to be really good at code review. So I can have something crunched by cheaper models, reviewed async by codex and then re-prompt with the findings from the review. It finds good things, doesn't flag nits (if prompted not to) and the overall flow is worth it for me. Speed loss doesn't impact this flow that much.
Personally, I have Claude do the coding. Then 5.2-high do the reviewing.
I think Anthropic rushed out the release before 10am this morning to avoid having to put in comparisons to GPT-5.3-codex! 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.
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I do not trust the AI benchmarks much, they often do not line up with my experience. That said ... I do think Codex 5.2 was the best coding model for more complex tasks, albeit quite slow. So very much looking forward to trying out 5.3.
Another day, another hn thread of "this model changes everything" followed immediately by a reply stating "actually I have the literal opposite experience and find competitor's model is the best" repeated until it's time to start the next day's thread.
Earlier quoted context omitted.
I do not trust the AI benchmarks much, they often do not line up with my experience. That said ... I do think Codex 5.2 was the best coding model for more complex tasks, albeit quite slow. So very much looking forward to trying out 5.3.
Another day, another hn thread of "this model changes everything" followed immediately by a reply stating "actually I have the literal opposite experience and find competitor's model is the best" repeated until it's time to start the next day's thread.
Earlier quoted context omitted.
I wish they’d just stop pretending to care about safety, other than a few researchers at the top they care about safety only as long as they aren’t losing ground to the competition. Game theory guarantees the AI labs will do what it takes to ensure survival. Only regulation can enforce the limits, self policing won’t work when money is involved.
As long as China continues to blitz forward, regulation is a direct path to losing.
I think Anthropic rushed out the release before 10am this morning to avoid having to put in comparisons to GPT-5.3-codex! 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.
they tested it at xhigh reasoning though, which is probably double the cost of Anthropic's model. Cost to Run Artificial Analysis Intelligence Index: GPT-5.2 Codex (xhigh): $3244 Claude Opus 4.5-reasoning: $1485 (and probably similar values for the newer models?)
Terminal Bench 2.0 | Name | Score | |---------------------|-------| | OpenAI Codex 5.3 | 77.3 | | Anthropic Opus 4.6 | 65.4 |
yea but i feel like we are over the hill on benchmaxxing, many times a model has beaten anthropic on a specific bench, but the 'feel' is that it is still not as good at coding
I think Anthropic rushed out the release before 10am this morning to avoid having to put in comparisons to GPT-5.3-codex! 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.