Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Llama 4 Behemoth finishes one point ahead overall, 44 to 43. 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 gives you the larger context window at 128K, compared with 32K for Llama 4 Behemoth.
Pick Llama 4 Behemoth if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority or you need the larger 128K context window.
Llama 4 Behemoth
40
GPT-4o mini
82
Llama 4 Behemoth
22.7
GPT-4o mini
87.2
Llama 4 Behemoth
66
GPT-4o mini
87
Llama 4 Behemoth is ahead overall, 44 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 40 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 40. 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 22.7. 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 66. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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