DeepSeek-R1
by Hangzhou DeepSeek CorporationDeepSeek-R1 is a high-performance AI reasoning model developed by Hangzhou DeepSeek Corporation. It is designed to match the capabilities of OpenAI's o1 official version, excelling in tasks such as math, coding, and natural language reasoning. The model leverages large-scale reinforcement learning techniques, achieving exceptional performance with minimal labeled data. DeepSeek-R1 is open-sourced under the MIT License and supports model distillation for training other models.
DeepSeek-R1: High-Performance AI Reasoning Model
What is DeepSeek-R1?
DeepSeek-R1 is a high-performance AI reasoning model developed by Hangzhou DeepSeek Corporation. It is designed to match the capabilities of OpenAI's o1 official version, excelling in tasks such as math, coding, and natural language reasoning. The model leverages large-scale reinforcement learning techniques, achieving exceptional performance with minimal labeled data. DeepSeek-R1 is open-sourced under the MIT License and supports model distillation for training other models.
Key Features of DeepSeek-R1
- High-Performance Reasoning: Excels in tasks like math, coding, and natural language reasoning, matching the performance of OpenAI's o1 official version.
- Reinforcement Learning with Minimal Data: Trained using reinforcement learning techniques with minimal labeled data, significantly enhancing reasoning capabilities.
- Model Distillation Support: Allows users to distill the model's outputs to train smaller models tailored for specific applications.
- Open Source with Flexible Licensing: Released under the MIT License, enabling free use, modification, and commercialization.
Technical Principles of DeepSeek-R1
- Reinforcement Learning-Driven Reasoning: DeepSeek-R1 extensively applies reinforcement learning during post-training, significantly improving reasoning capabilities with minimal labeled data.
- Chain-of-Thought (CoT) Reasoning: Utilizes long-chain reasoning techniques, enabling the model to decompose complex problems into multi-step logical processes, enhancing efficiency in complex tasks.
- Model Distillation: Supports model distillation, allowing developers to transfer DeepSeek-R1's powerful reasoning capabilities into lighter models for various applications.
Project Links
- GitHub Repository: https://github.com/deepseek-ai/DeepSeek-R1
- HuggingFace Model Hub: 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: Visit the DeepSeek official website or app, enable the "Deep Thinking" mode, and directly use DeepSeek-R1 for various reasoning tasks.
- API Service: DeepSeek-R1 offers API services, accessible by setting
model='deepseek-reasoner'. - Pricing:
- Input tokens: ¥1 per million (cache hit) / ¥4 per million (cache miss)
- Output tokens: ¥16 per million
Applications of DeepSeek-R1
- Research & Development: DeepSeek-R1 excels in complex tasks like math reasoning, code generation, and natural language processing, making it ideal for scenarios requiring large-scale reasoning and logical processing.
- Natural Language Processing (NLP): Provides strong technical support for NLP tasks such as natural language understanding, automated reasoning, and semantic analysis.
- Enterprise Intelligence: Enterprises can integrate DeepSeek-R1 into their products for applications like intelligent customer service, automated decision-making, and personalized recommendations.
- Education & Training: Serves as an educational tool to help students master complex reasoning methods, enhancing understanding in subjects like math and programming.
- Data Analysis & Decision Support: Handles complex logical reasoning tasks, supporting data analysis, market forecasting, and strategic decision-making in businesses.
Model Capabilities
Model Type
language
Supported Tasks
Math Reasoning
Coding
Natural Language Reasoning
Model Distillation
Tags
AI Reasoning
Reinforcement Learning
Model Distillation
Natural Language Processing
Math Reasoning
Coding
Open Source
MIT License
Chain-of-Thought Reasoning
API Integration
Usage & Integration
Pricing
paid
Input tokens: ¥1 per million (cache hit) / ¥4 per million (cache miss), Output tokens: ¥16 per million
API Access
Available
License
Open Source
MIT
Screenshots & Images
Primary Screenshot
Additional Images
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