Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
79
Qwen 3.6 Max (preview)
78
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen 3.6 Max (preview) only becomes the better choice if agentic is the priority.
Agentic
+10.2 difference
Coding
+10.6 difference
Knowledge
+18.5 difference
GPT-5.2
Qwen 3.6 Max (preview)
$1.75 / $14
N/A
73 t/s
N/A
130.34s
N/A
400K
256K
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen 3.6 Max (preview) only becomes the better choice if agentic is the priority.
GPT-5.2 finishes one point ahead on BenchLM's provisional leaderboard, 79 to 78. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 73.9. The single biggest benchmark swing on the page is SWE-bench Pro, 55.6% to 57.3%. Qwen 3.6 Max (preview) does hit back in agentic, so the answer changes if that is the part of the workload you care about most.
GPT-5.2 gives you the larger context window at 400K, compared with 256K for Qwen 3.6 Max (preview).
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 79 to 78. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 55.6% and 57.3%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 73.9. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
GPT-5.2 has the edge for coding in this comparison, averaging 64.7 versus 54.1. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Qwen 3.6 Max (preview) has the edge for agentic tasks in this comparison, averaging 65.4 versus 55.2. Inside this category, Tau2-Telecom is the benchmark that creates the most daylight between them.
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