Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
DeepSeek V3.2 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.
DeepSeek V3.2's sharpest advantage is in coding, where it averages 53.3 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 DeepSeek V3.2 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 DeepSeek V3.2.
Pick DeepSeek V3.2 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.
DeepSeek V3.2
68.5
o3-mini
82.1
DeepSeek V3.2
53.3
o3-mini
49.3
DeepSeek V3.2
82.8
o3-mini
87.3
DeepSeek V3.2
85
o3-mini
93.9
DeepSeek V3.2 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 68.5. Inside this category, GPQA is the benchmark that creates the most daylight between them.
DeepSeek V3.2 has the edge for coding in this comparison, averaging 53.3 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 82.8. 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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