DeepSeek R1
DeepSeek R1 is a reasoning-focused large language model released in January 2025 that pioneered reinforcement learning with verifiable rewards (RLVR) for post-training, achieving state-of-the-art performance on benchmarks like AIME 2024 and CodeForces while requiring significantly lower training costs ($5 million for full development, $294,000 for post-training) than previous estimates. The model's success has influenced industry-wide adoption of reasoning-based post-training approaches, and DeepSeek demonstrated that step-by-step reasoning traces from R1 can be distilled into smaller models that develop emergent reasoning abilities without reinforcement learning. R1 has become a reference model for the open-source AI community, with projects like Open R1 replicating its training pipeline and generating synthetic reasoning datasets across mathematics and other domains.
Updated 3 August 2026
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August 2026
July 2026
December 2025
Researcher compiles curated list of LLM research papers from July-December 2025 Research publication
November 2025
October 2025
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June 2025
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March 2025
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January 2025
Hugging Face releases tutorials and open-source projects replicating DeepSeek R1's reinforcement learning training methodology Open source release
Relationships
Products & technology
- DeepSeek develops this model · 4 sources
- Derived from DeepSeek 32B · 1 source
- Derived from DeepSeek 7B · 1 source
- Open-R1 derived from this model · 1 source
- OpenR1-Math-220k derived from this model · 1 source
- Hugging Face integrated with this model · 1 source