Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Kimi K2.5 (Reasoning) is clearly ahead on the aggregate, 82 to 28. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in coding, where it averages 69 against 54.8. The single biggest benchmark swing on the page is HumanEval, 84 to 54.8.
Kimi K2.5 (Reasoning) 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. Kimi K2.5 (Reasoning) gives you the larger context window at 128K, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Kimi K2.5 (Reasoning)
77.3
Mixtral 8x22B Instruct v0.1
71.4
Kimi K2.5 (Reasoning)
69
Mixtral 8x22B Instruct v0.1
54.8
Kimi K2.5 (Reasoning) is ahead overall, 82 to 28. The biggest single separator in this matchup is HumanEval, where the scores are 84 and 54.8.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 77.3 versus 71.4. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 69 versus 54.8. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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