Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.5
77
GPT-4.1 mini
46
Verified leaderboard positions: Claude Opus 4.5 #9 · GPT-4.1 mini unranked
Pick Claude Opus 4.5 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if instruction following is the priority or you want the cheaper token bill.
Coding
+42.3 difference
Knowledge
+2.0 difference
Inst. Following
+9.1 difference
Claude Opus 4.5
GPT-4.1 mini
$5 / $25
$0.4 / $1.6
46 t/s
80 t/s
1.01s
0.76s
200K
1M
Pick Claude Opus 4.5 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if instruction following is the priority or you want the cheaper token bill.
Claude Opus 4.5 is clearly ahead on the provisional aggregate, 77 to 46. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.5's sharpest advantage is in coding, where it averages 65.9 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 80.9% to 23.6%. GPT-4.1 mini does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
Claude Opus 4.5 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.40 input / $1.60 output per 1M tokens for GPT-4.1 mini. That is roughly 15.6x on output cost alone. GPT-4.1 mini gives you the larger context window at 1M, compared with 200K for Claude Opus 4.5.
Claude Opus 4.5 is ahead on BenchLM's provisional leaderboard, 77 to 46. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 80.9% and 23.6%.
Claude Opus 4.5 has the edge for knowledge tasks in this comparison, averaging 66.2 versus 64.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Claude Opus 4.5 has the edge for coding in this comparison, averaging 65.9 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 79.4. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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