Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.3 Codex
87
Qwen3.7 Max
93
Verified leaderboard positions: GPT-5.3 Codex unranked · Qwen3.7 Max #2
Pick Qwen3.7 Max if you want the stronger benchmark profile. GPT-5.3 Codex only becomes the better choice if agentic is the priority.
Agentic
+1.8 difference
Coding
+10.5 difference
GPT-5.3 Codex
Qwen3.7 Max
$1.75 / $14
$null / $null
79 t/s
N/A
88.26s
N/A
400K
1M
Pick Qwen3.7 Max if you want the stronger benchmark profile. GPT-5.3 Codex only becomes the better choice if agentic is the priority.
Qwen3.7 Max is clearly ahead on the provisional aggregate, 93 to 87. 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 63.1. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 77.3% to 69.7%. GPT-5.3 Codex does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
Qwen3.7 Max gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
Qwen3.7 Max is ahead on BenchLM's provisional leaderboard, 93 to 87. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 69.7%.
Qwen3.7 Max has the edge for coding in this comparison, averaging 73.6 versus 63.1. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.5 versus 69.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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