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DeepSeek R1

DeepSeek R1
2 min read
DeepSeek R1

DeepSeek R1, which DeepSeek shipped on January 20, 2025, is an MIT-licensed open-weights reasoning model that matched OpenAI's o1 on math and coding at a fraction of the price.

  • Model: DeepSeek R1 (deepseek-reasoner)

  • Maker: DeepSeek

  • Ship date: January 20, 2025

  • Pricing: $0.55 / $2.19 per M tokens

  • Context: 128K tokens (64K on DeepSeek's own API)

  • Where you can use it:

  • When to reach for it:

    • Math, code and logic that need reasoning

    • o1-class answers on a tight budget

    • Skip it for factual recall or fast replies

  • How it compares:

    • Ties o1 on math, trails it on science QA

    • Well ahead of o1-mini, and far cheaper

  • What makes it different:

    • Reasoning learned mostly via large-scale RL

    • MIT license; outputs OK for distillation

    • Shows its full chain of thought

  • Early reactions: Marc Andreessen called it AI's "Sputnik moment," and the release helped set off a sharp sell-off in Nvidia and other AI stocks.

  • Read more: DeepSeek-R1 Release, technical report

The benchmarks

DeepSeek's own runs with a 32,768-token generation cap and pass@1 averaged over 64 samples where sampling applies; it compared against o1 (December 17 build), o1-mini and Claude 3.5 Sonnet (October 2024), with rival scores as DeepSeek printed them.

DeepSeek's numbers

  • AIME 2024 (competition math): 79.8%. +0.6 over o1 (79.2%), +16.2 over o1-mini (63.6%).

  • MATH-500 (math problem solving): 97.3%. +0.9 over o1 (96.4%), +7.3 over o1-mini (90.0%).

  • GPQA Diamond (PhD-level science): 71.5%. −4.2 under o1 (75.7%), +11.5 over o1-mini (60.0%).

  • LiveCodeBench (fresh coding problems): 65.9%. +2.5 over o1 (63.4%), +12.1 over o1-mini (53.8%).

  • SWE-bench Verified (real GitHub fixes): 49.2%. +0.3 over o1 (48.9%), +7.6 over o1-mini (41.6%), −1.6 under Claude 3.5 Sonnet (50.8%).

  • Codeforces (competitive programming rating): 2029. −32 under o1 (2061), +209 over o1-mini (1820).

  • SimpleQA (short factual recall): 30.1%. −16.9 under o1 (47.0%), +23.1 over o1-mini (7.0%).

Independent numbers

  • Artificial Analysis Intelligence Index (current v4.3.2): 11.4. −3.8 under o1 (15.2), +1.6 over o1-mini (9.8).

  • ARC-AGI-1 (novel visual puzzles): 15.8%. −4.7 under o1 (low) (20.5%), −19.2 under o1 (high) (35%).

  • Aider Polyglot (multi-language code edits): 56.9%. −4.8 under o1 (high) (61.7%), +24.0 over o1-mini (32.9%), +5.3 over Claude 3.5 Sonnet (51.6%).

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