Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
Qwen2.5-1M is clearly ahead on the aggregate, 73 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Qwen2.5-1M gives you the larger context window at 1M, compared with 128K for GPT-4o mini.
Pick Qwen2.5-1M if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority.
Qwen2.5-1M
68.5
GPT-4o mini
82
Qwen2.5-1M
54.3
GPT-4o mini
87.2
Qwen2.5-1M
81
GPT-4o mini
87
Qwen2.5-1M is ahead overall, 73 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 76 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 68.5. 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 54.3. 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 81. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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