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Llama 3.1 Instruct 405B vs o1-mini

Meta · released

Wins 0 of 2 areas

—

OpenAI · released

Wins 1 of 2 areas

Coding

o1-mini wins more areas, narrowly.

Scores updated · 27 tests both models report · How we compare

Where each one wins

Tests won in each of the two areas 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.

The biggest differences

The tests each model wins by the widest margin, up to three each. Scores are out of 100.

Where o1-mini pulls ahead

  • Fixes real GitHub issues in Python projectsSWE-bench Verified+17.1points aheado1-mini41.6Llama 3.1 Instruct 405B24.5
  • Graduate-level biology, physics and chemistry questionsGPQA Diamond+8.8points aheado1-mini60.3Llama 3.1 Instruct 405B51.5
  • Code for real scientific research problemsSciCode+2.4points aheado1-mini32.3Llama 3.1 Instruct 405B29.9

Where Llama 3.1 Instruct 405B pulls ahead

  • Common-sense trick questionsSimpleBench+4.9points aheadLlama 3.1 Instruct 405B23o1-mini18.1

Every test, side by side

All 27 tests both models report. The winning score is in its model's colour; marks a score checked independently.

Codingo1-mini

Full coding ranking

ReasoningEven

Full reasoning ranking

Other results22 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.

Questions people ask

Which is better, Llama 3.1 Instruct 405B or o1-mini?

o1-mini wins one of the two areas where both have results: coding. Llama 3.1 Instruct 405B wins none. They are level on reasoning.

Which is better for coding?

o1-mini. It wins 2 of the 2 coding tests both models report; Llama 3.1 Instruct 405B wins none.

How do you compare the two?

We use the 27 benchmark tests both models have published scores on. The verdict counts the 5 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 22 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.