Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 mini is clearly ahead on the aggregate, 35 to 28. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1 mini's sharpest advantage is in knowledge, where it averages 75.9 against 71.4. The single biggest benchmark swing on the page is MMLU, 87.5 to 71.4. Mixtral 8x22B Instruct v0.1 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 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. GPT-4.1 mini gives you the larger context window at 1M, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick GPT-4.1 mini if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-4.1 mini
75.9
Mixtral 8x22B Instruct v0.1
71.4
GPT-4.1 mini
23.6
Mixtral 8x22B Instruct v0.1
54.8
GPT-4.1 mini is ahead overall, 35 to 28. The biggest single separator in this matchup is MMLU, where the scores are 87.5 and 71.4.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 71.4. 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 23.6. GPT-4.1 mini stays close enough that the answer can still flip depending on your workload.
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