Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-5.3 Codex is clearly ahead on the aggregate, 92 to 28. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex's sharpest advantage is in coding, where it averages 88.3 against 54.8. The single biggest benchmark swing on the page is HumanEval, 95 to 54.8.
GPT-5.3 Codex is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Mixtral 8x22B Instruct v0.1. That is roughly Infinityx on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while Mixtral 8x22B Instruct v0.1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-5.3 Codex gives you the larger context window at 400K, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick GPT-5.3 Codex if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.3 Codex
86.3
Mixtral 8x22B Instruct v0.1
71.4
GPT-5.3 Codex
88.3
Mixtral 8x22B Instruct v0.1
54.8
GPT-5.3 Codex is ahead overall, 92 to 28. The biggest single separator in this matchup is HumanEval, where the scores are 95 and 54.8.
GPT-5.3 Codex has the edge for knowledge tasks in this comparison, averaging 86.3 versus 71.4. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for coding in this comparison, averaging 88.3 versus 54.8. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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