Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Gemini 3.1 Pro is clearly ahead on the aggregate, 89 to 28. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro's sharpest advantage is in coding, where it averages 79 against 54.8. The single biggest benchmark swing on the page is HumanEval, 91 to 54.8.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Mixtral 8x22B Instruct v0.1. That is roughly Infinityx on output cost alone. Gemini 3.1 Pro gives you the larger context window at 1M, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if you want the cheaper token bill.
Gemini 3.1 Pro
86
Mixtral 8x22B Instruct v0.1
71.4
Gemini 3.1 Pro
79
Mixtral 8x22B Instruct v0.1
54.8
Gemini 3.1 Pro is ahead overall, 89 to 28. The biggest single separator in this matchup is HumanEval, where the scores are 91 and 54.8.
Gemini 3.1 Pro has the edge for knowledge tasks in this comparison, averaging 86 versus 71.4. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Gemini 3.1 Pro has the edge for coding in this comparison, averaging 79 versus 54.8. Inside this category, HumanEval 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.