Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
DeepSeek V3.2 (Thinking) is clearly ahead on the aggregate, 75 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek V3.2 (Thinking) is the reasoning model in the pair, while GPT-4o mini 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.
Pick DeepSeek V3.2 (Thinking) if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
DeepSeek V3.2 (Thinking)
71.8
GPT-4o mini
82
DeepSeek V3.2 (Thinking)
57.3
GPT-4o mini
87.2
DeepSeek V3.2 (Thinking)
84
GPT-4o mini
87
DeepSeek V3.2 (Thinking) is ahead overall, 75 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 79 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 71.8. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 57.3. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 87 versus 84. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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