What is DeepSeek-R1
DeepSeek-R1 is developed by Hangzhou DeepSeek Company DeepSeek It is a high-performance AI reasoning model, benchmarked against the official OpenAI o1 release. The DeepSeek-R1 reasoning model is post-trained through large-scale reinforcement learning technology. With only a very small amount of labeled data, it achieves outstanding performance on tasks such as mathematics, code, and natural language reasoning. DeepSeek-R1 is open-sourced under the MIT License and supports model distillation to train other models.
Main features of DeepSeek-R1
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High-performance reasoning capability: It performs excellently on tasks such as mathematics, code, and natural language reasoning, with performance comparable to the official OpenAI o1 release.
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Reinforcement learning and a small amount of labeled data: It is trained through reinforcement learning technology and a very small amount of labeled data, significantly improving the model's reasoning capability.
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Model distillation support: It supports users in using the output of DeepSeek-R1 for model distillation to train smaller models, meeting the needs of specific application scenarios.
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Open source and flexible license: It is open-sourced under the MIT License, and users can freely use, modify, and commercialize it.
Technical principles of DeepSeek-R1
- Reinforcement learning-driven improvement of reasoning capability: DeepSeek-R1 extensively applies reinforcement learning technology in the post-training stage. Through reinforcement learning, the model can significantly improve its reasoning capability with only a very small amount of labeled data. This enables the model to perform excellently on tasks such as mathematics, code, and natural language reasoning, with performance comparable to the official OpenAI o1 release.
- Long chain reasoning (Chain-of-Thought, CoT): DeepSeek-R1 adopts long chain reasoning technology, and its chain of thought can reach tens of thousands of words. This enables the model to decompose complex problems step by step and solve them through multi-step logical reasoning, demonstrating higher efficiency in complex tasks.
- Model distillation technology: DeepSeek-R1 supports model distillation and allows users to use its output to train smaller models. In this way, developers can inject the powerful reasoning capability of DeepSeek-R1 into more lightweight models to meet the needs of different application scenarios.
Project address of DeepSeek-R1
- GitHub repository：https://github.com/deepseek-ai/DeepSeek-R1
- HuggingFace model library：https://huggingface.co/deepseek-ai/DeepSeek-R1
- Technical paper：https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf
How to use DeepSeek-R1
- Official website experience: You can log in to DeepSeek official websiteor the official App, open "Deep Think" mode, and directly call DeepSeek-R1 to complete various reasoning tasks.
- API service: DeepSeek-R1 provides API interface services. Users can call the model by setting model='deepseek-reasoner'.
- Pricing: Per million input tokens: 1 yuan (cache hit) / 4 yuan (cache miss). Per million output tokens: 16 yuan.
Application scenarios of DeepSeek-R1
- Scientific research and technical development: DeepSeek-R1 performs excellently in complex tasks such as mathematical reasoning, code generation, and natural language reasoning, with performance comparable to the official OpenAI o1 release. It is suitable for scenarios requiring large-scale reasoning and complex logical processing, such as mathematical modeling, algorithm optimization, and engineering technology research.
- Natural language processing (NLP): The model performs outstandingly in tasks such as natural language understanding, automated reasoning, and semantic analysis, and can provide strong technical support for the field of natural language processing, promoting the further development of NLP technology.
- Enterprise Intelligent Upgrading: Enterprises can integrate the model into their own products through the DeepSeek-R1 API service, applying it to scenarios such as intelligent customer service, automated decision-making, and personalized recommendations.
- Education and Training: DeepSeek-R1 can serve as an educational tool, helping students master complex reasoning methods and promoting learners' deep understanding in subjects such as mathematics and programming. Its long reasoning chains and detailed displays of the thinking process can provide more intuitive teaching support for educational scenarios.
- Data Analysis and Intelligent Decision-Making: DeepSeek-R1 can handle complex logical reasoning tasks and is suitable for data analysis and intelligent decision support systems. Its reasoning ability can provide strong support for enterprises' data analysis, market forecasting, and strategy formulation.