Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Claude Sonnet 4.5 is clearly ahead on the aggregate, 83 to 32. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Sonnet 4.5's sharpest advantage is in knowledge, where it averages 78.8 against 73.7. The single biggest benchmark swing on the page is MMLU, 95 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.
Claude Sonnet 4.5 is also the more expensive model on tokens at $3.00 input / $15.00 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. Claude Sonnet 4.5 gives you the larger context window at 200K, compared with 32K for DBRX Instruct.
Pick Claude Sonnet 4.5 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.
Claude Sonnet 4.5
78.8
DBRX Instruct
73.7
Claude Sonnet 4.5
68.7
DBRX Instruct
70.1
Claude Sonnet 4.5 is ahead overall, 83 to 32. The biggest single separator in this matchup is MMLU, where the scores are 95 and 73.7.
Claude Sonnet 4.5 has the edge for knowledge tasks in this comparison, averaging 78.8 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 68.7. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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