Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Haiku 4.5
58
GPT-4.1 mini
46
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Coding
+49.7 difference
Claude Haiku 4.5
GPT-4.1 mini
$1 / $5
$0.4 / $1.6
N/A
80 t/s
N/A
0.76s
200K
1M
Pick Claude Haiku 4.5 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Claude Haiku 4.5 is clearly ahead on the provisional aggregate, 58 to 46. 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 coding, where it averages 73.3 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 73.3% to 23.6%.
Claude Haiku 4.5 is also the more expensive model on tokens at $1.00 input / $5.00 output per 1M tokens, versus $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. That is roughly 3.1x on output cost alone. GPT-4.1 mini gives you the larger context window at 1M, compared with 200K for Claude Haiku 4.5.
Claude Haiku 4.5 is ahead on BenchLM's provisional leaderboard, 58 to 46. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 73.3% and 23.6%.
Claude Haiku 4.5 has the edge for coding in this comparison, averaging 73.3 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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