Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Qwen2.5-72B is clearly ahead on the aggregate, 72 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-72B's sharpest advantage is in coding, where it averages 53.7 against 49.3. The single biggest benchmark swing on the page is IFEval, 85 to 93.9. o3-mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
o3-mini is the reasoning model in the pair, while Qwen2.5-72B 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. o3-mini gives you the larger context window at 200K, compared with 128K for Qwen2.5-72B.
Pick Qwen2.5-72B if you want the stronger benchmark profile. o3-mini only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
Qwen2.5-72B
68.2
o3-mini
82.1
Qwen2.5-72B
53.7
o3-mini
49.3
Qwen2.5-72B
83.1
o3-mini
87.3
Qwen2.5-72B
85
o3-mini
93.9
Qwen2.5-72B is ahead overall, 72 to 56. The biggest single separator in this matchup is IFEval, where the scores are 85 and 93.9.
o3-mini has the edge for knowledge tasks in this comparison, averaging 82.1 versus 68.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Qwen2.5-72B has the edge for coding in this comparison, averaging 53.7 versus 49.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
o3-mini has the edge for math in this comparison, averaging 87.3 versus 83.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 85. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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