Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Claude Haiku 4.5 is clearly ahead on the aggregate, 64 to 28. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Haiku 4.5 is also the more expensive model on tokens at $0.80 input / $4.00 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. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Claude Haiku 4.5
57.8
Mixtral 8x22B Instruct v0.1
71.4
Claude Haiku 4.5
48
Mixtral 8x22B Instruct v0.1
54.8
Claude Haiku 4.5 is ahead overall, 64 to 28. The biggest single separator in this matchup is HumanEval, where the scores are 60 and 54.8.
Mixtral 8x22B Instruct v0.1 has the edge for knowledge tasks in this comparison, averaging 71.4 versus 57.8. 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 48. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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