Skip to content
VECTOR WIREAI INTELLIGENCE
UTC

Llama 3 (70B) vs Qwen2 7B Instruct

Meta

Wins 1 of 1 area

Reasoning

Alibaba · released

Wins 0 of 1 area

—

Llama 3 (70B) 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 Llama 3 (70B) pulls ahead

  • Graduate-level biology, physics and chemistry questionsGPQA Diamond+11points aheadLlama 3 (70B)36.3Qwen2 7B Instruct25.3

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.

ReasoningLlama 3 (70B)

Full reasoning ranking

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 31.748.279.9+31.7
  • EvalPlusQwen2 7B Instruct by 15.554.870.3+15.5
  • MultiPL-EQwen2 7B Instruct by 12.846.359.1+12.8
  • C-EvalQwen2 7B Instruct by 1265.277.2+12
  • MMLU-ProLlama 3 (70B) by 8.752.844.1+8.7
  • Theorem QALlama 3 (70B) by 732.325.3+7
  • MBPPLlama 3 (70B) by 3.270.467.2+3.2
  • GSM8KQwen2 7B Instruct by 1.880.582.3+1.8

Questions people ask

Which is better, Llama 3 (70B) or Qwen2 7B Instruct?

Llama 3 (70B) 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.