Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
DeepSeekMath V2 is clearly ahead on the aggregate, 71 to 28. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeekMath V2 is the reasoning model in the pair, while Mixtral 8x22B Instruct v0.1 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. DeepSeekMath V2 gives you the larger context window at 128K, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick DeepSeekMath V2 if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
DeepSeekMath V2
67.2
Mixtral 8x22B Instruct v0.1
71.4
DeepSeekMath V2
53.7
Mixtral 8x22B Instruct v0.1
54.8
DeepSeekMath V2 is ahead overall, 71 to 28. The biggest single separator in this matchup is HumanEval, where the scores are 72 and 54.8.
Mixtral 8x22B Instruct v0.1 has the edge for knowledge tasks in this comparison, averaging 71.4 versus 67.2. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Mixtral 8x22B Instruct v0.1 has the edge for coding in this comparison, averaging 54.8 versus 53.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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