Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4o mini finishes one point ahead overall, 43 to 42. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-4o mini's sharpest advantage is in coding, where it averages 87.2 against 22. The single biggest benchmark swing on the page is HumanEval, 87.2 to 38.
GPT-4o mini is also the more expensive model on tokens at $0.15 input / $0.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Llama 4 Maverick. That is roughly Infinityx on output cost alone. Llama 4 Maverick gives you the larger context window at 1M, compared with 128K for GPT-4o mini.
Pick GPT-4o mini if you want the stronger benchmark profile. Llama 4 Maverick only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
GPT-4o mini
82
Llama 4 Maverick
38.7
GPT-4o mini
87.2
Llama 4 Maverick
22
GPT-4o mini
87
Llama 4 Maverick
63
GPT-4o mini is ahead overall, 43 to 42. The biggest single separator in this matchup is HumanEval, where the scores are 87.2 and 38.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 38.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 22. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 87 versus 63. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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