Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-5.3 Codex is clearly ahead on the aggregate, 92 to 23. 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 mathematics, where it averages 97.4 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 99 to 9.8.
GPT-5.3 Codex is also the more expensive model on tokens at $2.50 input / $10.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 25.0x on output cost alone. GPT-5.3 Codex is the reasoning model in the pair, while GPT-4.1 nano 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-4.1 nano gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
Pick GPT-5.3 Codex if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-5.3 Codex
86.3
GPT-4.1 nano
65.2
GPT-5.3 Codex
97.4
GPT-4.1 nano
9.8
GPT-5.3 Codex
93
GPT-4.1 nano
83.2
GPT-5.3 Codex is ahead overall, 92 to 23. The biggest single separator in this matchup is AIME 2024, where the scores are 99 and 9.8.
GPT-5.3 Codex has the edge for knowledge tasks in this comparison, averaging 86.3 versus 65.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for math in this comparison, averaging 97.4 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for instruction following in this comparison, averaging 93 versus 83.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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