Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.4
89
Qwen3.7 Max
93
Verified leaderboard positions: GPT-5.4 #14 · Qwen3.7 Max #2
Pick Qwen3.7 Max if you want the stronger benchmark profile. GPT-5.4 only becomes the better choice if agentic is the priority or you need the larger 1.05M context window.
Agentic
+7.3 difference
Coding
+15.9 difference
Knowledge
+5.1 difference
GPT-5.4
Qwen3.7 Max
$2.5 / $15
$null / $null
74 t/s
N/A
151.79s
N/A
1.05M
1M
Pick Qwen3.7 Max if you want the stronger benchmark profile. GPT-5.4 only becomes the better choice if agentic is the priority or you need the larger 1.05M context window.
Qwen3.7 Max is clearly ahead on the provisional aggregate, 93 to 89. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen3.7 Max's sharpest advantage is in coding, where it averages 73.6 against 57.7. The single biggest benchmark swing on the page is HLE, 52.1% to 41.4%. GPT-5.4 does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
GPT-5.4 gives you the larger context window at 1.05M, compared with 1M for Qwen3.7 Max.
Qwen3.7 Max is ahead on BenchLM's provisional leaderboard, 93 to 89. The biggest single separator in this matchup is HLE, where the scores are 52.1% and 41.4%.
Qwen3.7 Max has the edge for knowledge tasks in this comparison, averaging 71.2 versus 66.1. Inside this category, HLE is the benchmark that creates the most daylight between them.
Qwen3.7 Max has the edge for coding in this comparison, averaging 73.6 versus 57.7. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
GPT-5.4 has the edge for agentic tasks in this comparison, averaging 77 versus 69.7. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
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