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's sharpest advantage is in mathematics, where it averages 80.1 against 26.4. The single biggest benchmark swing on the page is AIME 2024, 83 to 26.4. GPT-4.1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek Coder 2.0. That is roughly 7.3x on output cost alone. GPT-4.1 gives you the larger context window at 1M, compared with 128K for DeepSeek Coder 2.0.
Pick DeepSeek Coder 2.0 if you want the stronger benchmark profile. GPT-4.1 only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
DeepSeek Coder 2.0
66.3
GPT-4.1
78.3
DeepSeek Coder 2.0
59.3
GPT-4.1
54.6
DeepSeek Coder 2.0
80.1
GPT-4.1
26.4
DeepSeek Coder 2.0
86
GPT-4.1
87.4
DeepSeek Coder 2.0 is ahead overall, 73 to 43. The biggest single separator in this matchup is AIME 2024, where the scores are 83 and 26.4.
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 78.3 versus 66.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for coding in this comparison, averaging 59.3 versus 54.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
DeepSeek Coder 2.0 has the edge for math in this comparison, averaging 80.1 versus 26.4. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 86. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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