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VECTOR WIREAI INTELLIGENCE
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DeepSeek-V2.5 vs o1-mini

DeepSeek · released

Wins 0 of 2 areas

—

OpenAI · released

Wins 2 of 2 areas

Coding · Reasoning

o1-mini is the stronger all-rounder.

Scores updated · 18 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.

Coding and reasoning rest on a single test each.

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+24.8points aheado1-mini41.6DeepSeek-V2.516.8
  • Graduate-level biology, physics and chemistry questionsGPQA Diamond+18points aheado1-mini60.3DeepSeek-V2.542.3

Where DeepSeek-V2.5 pulls ahead

No clear win on a test scored out of 100.

Every test, side by side

All 18 tests both models report. The winning score is in its model's colour; marks a score checked independently.

Codingo1-mini

Full coding ranking

Reasoningo1-mini

Full reasoning ranking

Other results16 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, DeepSeek-V2.5 or o1-mini?

o1-mini wins all two areas where both have results: coding and reasoning. DeepSeek-V2.5 wins none.

Which is better for coding?

o1-mini. It wins the one coding test both models report.

How do you compare the two?

We use the 18 benchmark tests both models have published scores on. The verdict counts the 2 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 16 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.