Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-5.2
83
Qwen3 235B 2507
35
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Knowledge
+16.2 difference
GPT-5.2
Qwen3 235B 2507
$2 / $8
$0 / $0
73 t/s
N/A
130.34s
N/A
400K
128K
Pick GPT-5.2 if you want the stronger benchmark profile. Qwen3 235B 2507 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 is clearly ahead on the provisional aggregate, 83 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2's sharpest advantage is in knowledge, where it averages 92.4 against 76.2. The single biggest benchmark swing on the page is GPQA, 92.4% to 77.5%.
GPT-5.2 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3 235B 2507. That is roughly Infinityx on output cost alone. GPT-5.2 is the reasoning model in the pair, while Qwen3 235B 2507 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-5.2 gives you the larger context window at 400K, compared with 128K for Qwen3 235B 2507.
GPT-5.2 is ahead on BenchLM's provisional leaderboard, 83 to 35. The biggest single separator in this matchup is GPQA, where the scores are 92.4% and 77.5%.
GPT-5.2 has the edge for knowledge tasks in this comparison, averaging 92.4 versus 76.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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