Head-to-head comparison across 6benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.7
86
GPT-5.5
89
Verified leaderboard positions: Claude Opus 4.7 #6 · GPT-5.5 #2
Pick GPT-5.5 if you want the stronger benchmark profile. Claude Opus 4.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Agentic
+6.9 difference
Coding
+14.3 difference
Reasoning
+9.2 difference
Knowledge
+1.8 difference
Math
+7.9 difference
Multimodal
+25.4 difference
Claude Opus 4.7
GPT-5.5
$5 / $25
$5 / $30
N/A
N/A
N/A
N/A
1M
1M
Pick GPT-5.5 if you want the stronger benchmark profile. Claude Opus 4.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.
GPT-5.5 has the cleaner provisional overall profile here, landing at 89 versus 86. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.5's sharpest advantage is in multimodal & grounded, where it averages 69 against 43.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 69.4% to 82.7%. Claude Opus 4.7 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.5 is also the more expensive model on tokens at $5.00 input / $30.00 output per 1M tokens, versus $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.7. GPT-5.5 is the reasoning model in the pair, while Claude Opus 4.7 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.
GPT-5.5 is ahead on BenchLM's provisional leaderboard, 89 to 86. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 69.4% and 82.7%.
Claude Opus 4.7 has the edge for knowledge tasks in this comparison, averaging 68.2 versus 66.4. Inside this category, HLE w/o tools is the benchmark that creates the most daylight between them.
Claude Opus 4.7 has the edge for coding in this comparison, averaging 72.9 versus 58.6. Inside this category, terminalBench2 is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for math in this comparison, averaging 51.7 versus 43.8. Inside this category, FrontierMath is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for reasoning in this comparison, averaging 85 versus 75.8. Inside this category, MRCR v2 128K-256K is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for agentic tasks in this comparison, averaging 81.8 versus 74.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.5 has the edge for multimodal and grounded tasks in this comparison, averaging 69 versus 43.6. Inside this category, OfficeQA Pro is the benchmark that creates the most daylight between them.
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