Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Mistral Large 3 is clearly ahead on the aggregate, 68 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mistral Large 3 is also the more expensive model on tokens at $2.00 input / $6.00 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for GPT-4o mini. That is roughly 10.0x on output cost alone.
Pick Mistral Large 3 if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority or you want the cheaper token bill.
Mistral Large 3
63.5
GPT-4o mini
82
Mistral Large 3
50.7
GPT-4o mini
87.2
Mistral Large 3
82
GPT-4o mini
87
Mistral Large 3 is ahead overall, 68 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 68 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 63.5. 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 50.7. 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 82. Inside this category, MGSM is the benchmark that creates the most daylight between them.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.