DeepSeek-V2 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-V2 pulls ahead
- Graduate-level biology, physics and chemistry questionsGPQA Diamond+10points ahead
Where Qwen2 7B 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.
- HumanEvalQwen2 7B Instruct by 36.643.379.9+36.6
- EvalPlusQwen2 7B Instruct by 15.35570.3+15.3
- LiveCodeBenchQwen2 7B Instruct by 1511.626.6+15
- MultiPL-EQwen2 7B Instruct by 14.744.459.1+14.7
- MMLU-ProDeepSeek-V2 by 7.351.444.1+7.3
- C-EvalDeepSeek-V2 by 4.281.477.2+4.2
- GSM8KQwen2 7B Instruct by 3.179.282.3+3.1
- MBPPQwen2 7B Instruct by 2.26567.2+2.2
Questions people ask
Which is better, DeepSeek-V2 or Qwen2 7B Instruct?
DeepSeek-V2 wins the one area where both have results: reasoning. Qwen2 7B 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.