Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
GPT-5.2 Pro is clearly ahead on the aggregate, 90 to 66. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.2 Pro's sharpest advantage is in coding, where it averages 84.8 against 44.8. The single biggest benchmark swing on the page is LiveCodeBench, 81 to 40.
GPT-5.2 Pro is the reasoning model in the pair, while Qwen2.5-1M 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. Qwen2.5-1M gives you the larger context window at 1M, compared with 400K for GPT-5.2 Pro.
Pick GPT-5.2 Pro if you want the stronger benchmark profile. Qwen2.5-1M only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
GPT-5.2 Pro
85.9
Qwen2.5-1M
64.7
GPT-5.2 Pro
84.8
Qwen2.5-1M
44.8
GPT-5.2 Pro
96
Qwen2.5-1M
68.4
GPT-5.2 Pro
95.2
Qwen2.5-1M
80.9
GPT-5.2 Pro
81.5
Qwen2.5-1M
60.4
GPT-5.2 Pro
95
Qwen2.5-1M
84
GPT-5.2 Pro
93.4
Qwen2.5-1M
80.4
GPT-5.2 Pro
98.2
Qwen2.5-1M
83.6
GPT-5.2 Pro is ahead overall, 90 to 66. The biggest single separator in this matchup is LiveCodeBench, where the scores are 81 and 40.
GPT-5.2 Pro has the edge for knowledge tasks in this comparison, averaging 81.5 versus 60.4. Inside this category, HLE is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for coding in this comparison, averaging 84.8 versus 44.8. Inside this category, LiveCodeBench is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for math in this comparison, averaging 98.2 versus 83.6. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for reasoning in this comparison, averaging 95.2 versus 80.9. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for agentic tasks in this comparison, averaging 85.9 versus 64.7. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 96 versus 68.4. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for instruction following in this comparison, averaging 95 versus 84. Inside this category, IFEval is the benchmark that creates the most daylight between them.
GPT-5.2 Pro has the edge for multilingual tasks in this comparison, averaging 93.4 versus 80.4. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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