Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Claude Haiku 4.5 is clearly ahead on the aggregate, 64 to 32. 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 DBRX Instruct. That is roughly Infinityx on output cost alone. Claude Haiku 4.5 gives you the larger context window at 200K, compared with 32K for DBRX Instruct.
Pick Claude Haiku 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 Haiku 4.5
57.8
DBRX Instruct
73.7
Claude Haiku 4.5
48
DBRX Instruct
70.1
Claude Haiku 4.5 is ahead overall, 64 to 32. The biggest single separator in this matchup is HumanEval, where the scores are 60 and 70.1.
DBRX Instruct has the edge for knowledge tasks in this comparison, averaging 73.7 versus 57.8. 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 48. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
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