Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
DeepSeek Coder 2.0 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.
DeepSeek Coder 2.0 is also the more expensive model on tokens at $0.27 input / $1.10 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for GPT-4o mini.
Pick DeepSeek Coder 2.0 if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority or you want the cheaper token bill.
DeepSeek Coder 2.0
66.3
GPT-4o mini
82
DeepSeek Coder 2.0
59.3
GPT-4o mini
87.2
DeepSeek Coder 2.0
83
GPT-4o mini
87
DeepSeek Coder 2.0 is ahead overall, 73 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 82 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 66.3. 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 59.3. 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 83. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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