Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4.1 mini has the cleaner overall profile here, landing at 35 versus 32. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4.1 mini's sharpest advantage is in knowledge, where it averages 75.9 against 73.7. The single biggest benchmark swing on the page is MMLU, 87.5 to 73.7. DBRX Instruct 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 DBRX Instruct. That is roughly Infinityx on output cost alone. GPT-4.1 mini gives you the larger context window at 1M, compared with 32K for DBRX Instruct.
Pick GPT-4.1 mini if you want the stronger benchmark profile. DBRX Instruct only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-4.1 mini
75.9
DBRX Instruct
73.7
GPT-4.1 mini
23.6
DBRX Instruct
70.1
GPT-4.1 mini is ahead overall, 35 to 32. The biggest single separator in this matchup is MMLU, where the scores are 87.5 and 73.7.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 73.7. Inside this category, MMLU is the benchmark that creates the most daylight between them.
DBRX Instruct has the edge for coding in this comparison, averaging 70.1 versus 23.6. GPT-4.1 mini stays close enough that the answer can still flip depending on your workload.
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