DeepSeek-V3.1-Base is the stronger all-rounder.
Scores updated · 9 tests both models report · How we compare
Where each one wins
Tests won in each of the one area where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
Reasoning rests on a single test.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where DeepSeek-V3.1-Base pulls ahead
- Graduate-level biology, physics and chemistry questionsGPQA Diamond+8.6points ahead
Where Hunyuan Large Instruct pulls ahead
No clear win on a test scored out of 100.
Every test, side by side
All 9 tests both models report. The winning score is in its model's colour; marks a score checked independently.
Other results8 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- HumanEvalHunyuan Large Instruct by 17.572.590+17.5
- MATHHunyuan Large Instruct by 14.862.677.4+14.8
- MMLUHunyuan Large Instruct by 2.587.489.9+2.5
- CMMLUHunyuan Large Instruct by 1.688.890.4+1.6
- C-EvalDeepSeek-V3.1-Base by 1.49088.6+1.4
- BBHHunyuan Large Instruct by 1.388.289.5+1.3
- ARC-ChallengeDeepSeek-V3.1-Base by 195.694.6+1
- HellaSwagtie89.288.5tie
Questions people ask
Which is better, DeepSeek-V3.1-Base or Hunyuan Large Instruct?
DeepSeek-V3.1-Base wins the one area where both have results: reasoning. Hunyuan Large Instruct wins none.
How do you compare the two?
We use the 9 benchmark tests both models have published scores on. The verdict counts the 1 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 8 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.