Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 42. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in knowledge, where it averages 82.1 against 38.7. The single biggest benchmark swing on the page is MMLU, 86.9 to 46.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 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. o3-mini is the reasoning model in the pair, while Llama 4 Maverick 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. Llama 4 Maverick gives you the larger context window at 1M, compared with 200K for o3-mini.
Pick o3-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.
o3-mini
82.1
Llama 4 Maverick
38.7
o3-mini
49.3
Llama 4 Maverick
22
o3-mini
87.3
Llama 4 Maverick
46.8
o3-mini
93.9
Llama 4 Maverick
68
o3-mini is ahead overall, 56 to 42. The biggest single separator in this matchup is MMLU, where the scores are 86.9 and 46.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 38.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
o3-mini has the edge for coding in this comparison, averaging 49.3 versus 22. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 46.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 68. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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