Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Mistral 8x7B v0.2 has the cleaner overall profile here, landing at 33 versus 31. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5 nano is the reasoning model in the pair, while Mistral 8x7B v0.2 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-5 nano gives you the larger context window at 400K, compared with 32K for Mistral 8x7B v0.2.
Pick Mistral 8x7B v0.2 if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if mathematics is the priority or you need the larger 400K context window.
Mistral 8x7B v0.2
27
GPT-5 nano
71.2
Mistral 8x7B v0.2
31.9
GPT-5 nano
85.2
Mistral 8x7B v0.2 is ahead overall, 33 to 31. The biggest single separator in this matchup is AIME 2025, where the scores are 30 and 85.2.
GPT-5 nano has the edge for knowledge tasks in this comparison, averaging 71.2 versus 27. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5 nano has the edge for math in this comparison, averaging 85.2 versus 31.9. Inside this category, AIME 2025 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.