Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
GPT-4o mini has the cleaner overall profile here, landing at 43 versus 40. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4o mini's sharpest advantage is in coding, where it averages 87.2 against 22. The single biggest benchmark swing on the page is HumanEval, 87.2 to 32.
Qwen3 235B 2507 (Reasoning) 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 GPT-4o mini if you want the stronger benchmark profile. Qwen3 235B 2507 (Reasoning) only becomes the better choice if you want the stronger reasoning-first profile.
GPT-4o mini
82
Qwen3 235B 2507 (Reasoning)
34.7
GPT-4o mini
87.2
Qwen3 235B 2507 (Reasoning)
22
GPT-4o mini
87
Qwen3 235B 2507 (Reasoning)
62
GPT-4o mini is ahead overall, 43 to 40. The biggest single separator in this matchup is HumanEval, where the scores are 87.2 and 32.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 34.7. 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 22. 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 62. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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