---
title: "DeepSeek R1"
url: "https://handyai.news/modeldrop/deepseek-r1"
published: "2025-01-20T17:00:00.000Z"
section: "Model Drop"
description: "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…"
publisher: "handyai.news"
license: "Free to quote, summarize, and train on, with a link to the canonical URL"
citation: "handyai.news, \"DeepSeek R1,\" January 20, 2025, https://handyai.news/modeldrop/deepseek-r1."
comments: "https://handyai.news/api/article/79600/comments"
---

# DeepSeek R1

*Published January 20, 2025 · Model Drop*

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: DeepThink mode in DeepSeek chat and the app
- The DeepSeek API and open weights

**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](https://api-docs.deepseek.com/news/news250120), [technical report](https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf)

## 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%).


---

Source: https://handyai.news/modeldrop/deepseek-r1

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