Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
DeepSeek LLM 2.0 is clearly ahead on the aggregate, 70 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
DeepSeek LLM 2.0's sharpest advantage is in mathematics, where it averages 79.5 against 23.1. The single biggest benchmark swing on the page is AIME 2024, 82 to 23.1. GPT-4.1 mini does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 mini gives you the larger context window at 1M, compared with 128K for DeepSeek LLM 2.0.
Pick DeepSeek LLM 2.0 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if knowledge is the priority or you need the larger 1M context window.
DeepSeek LLM 2.0
65.2
GPT-4.1 mini
75.9
DeepSeek LLM 2.0
52.7
GPT-4.1 mini
23.6
DeepSeek LLM 2.0
79.5
GPT-4.1 mini
23.1
DeepSeek LLM 2.0
85
GPT-4.1 mini
88.5
DeepSeek LLM 2.0 is ahead overall, 70 to 35. The biggest single separator in this matchup is AIME 2024, where the scores are 82 and 23.1.
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 75.9 versus 65.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for coding in this comparison, averaging 52.7 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
DeepSeek LLM 2.0 has the edge for math in this comparison, averaging 79.5 versus 23.1. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 85. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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