Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
Z-1 finishes one point ahead overall, 26 to 25. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Z-1's sharpest advantage is in reasoning, where it averages 48.9 against 24.9. The single biggest benchmark swing on the page is MMLU, 88.5% to 52%. DeepSeek V3 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Pick Z-1 if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if mathematics is the priority.
Benchmark data for this category is coming soon.
DeepSeek V3
42
Z-1
44
Benchmark data for this category is coming soon.
DeepSeek V3
24.9
Z-1
48.9
DeepSeek V3
69.6
Z-1
50
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
DeepSeek V3
90.2
Z-1
51
Z-1 is ahead overall, 26 to 25. The biggest single separator in this matchup is MMLU, where the scores are 88.5% and 52%.
DeepSeek V3 has the edge for knowledge tasks in this comparison, averaging 69.6 versus 50. Inside this category, MMLU is the benchmark that creates the most daylight between them.
Z-1 has the edge for coding in this comparison, averaging 44 versus 42. DeepSeek V3 stays close enough that the answer can still flip depending on your workload.
DeepSeek V3 has the edge for math in this comparison, averaging 90.2 versus 51. Inside this category, AIME 2024 is the benchmark that creates the most daylight between them.
Z-1 has the edge for reasoning in this comparison, averaging 48.9 versus 24.9. Inside this category, SimpleQA is the benchmark that creates the most daylight between them.
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