Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
o3-mini is clearly ahead on the aggregate, 56 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in knowledge, where it averages 82.1 against 73.7. The single biggest benchmark swing on the page is MMLU, 86.9 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.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 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. o3-mini is the reasoning model in the pair, while DBRX Instruct 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. o3-mini gives you the larger context window at 200K, compared with 32K for DBRX Instruct.
Pick o3-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.
o3-mini
82.1
DBRX Instruct
73.7
o3-mini
49.3
DBRX Instruct
70.1
o3-mini is ahead overall, 56 to 32. The biggest single separator in this matchup is MMLU, where the scores are 86.9 and 73.7.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 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 49.3. o3-mini stays close enough that the answer can still flip depending on your workload.
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