Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Claude Haiku 4.5 is clearly ahead on the aggregate, 64 to 23. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Haiku 4.5's sharpest advantage is in mathematics, where it averages 68.8 against 9.8. The single biggest benchmark swing on the page is AIME 2024, 70 to 9.8. GPT-4.1 nano does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
Claude Haiku 4.5 is also the more expensive model on tokens at $0.80 input / $4.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 10.0x on output cost alone. GPT-4.1 nano gives you the larger context window at 1M, compared with 200K for Claude Haiku 4.5.
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if knowledge is the priority or you want the cheaper token bill.
Claude Haiku 4.5
57.8
GPT-4.1 nano
65.2
Claude Haiku 4.5
68.8
GPT-4.1 nano
9.8
Claude Haiku 4.5
86
GPT-4.1 nano
83.2
Claude Haiku 4.5 is ahead overall, 64 to 23. The biggest single separator in this matchup is AIME 2024, where the scores are 70 and 9.8.
GPT-4.1 nano has the edge for knowledge tasks in this comparison, averaging 65.2 versus 57.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for math in this comparison, averaging 68.8 versus 9.8. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
Claude Haiku 4.5 has the edge for instruction following in this comparison, averaging 86 versus 83.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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