1. DeepSeek-V3: General-Purpose Chat Model
- Description: A 671-billion-parameter model optimized for natural language understanding, code generation, and long-context tasks. It employs a Mixture-of-Experts (MoE) architecture, activating only 3.7 billion parameters per query for efficiency .
- Performance: Matches GPT-4o and Claude-3.5-Sonnet in benchmarks, with a 3x faster inference speed than its predecessors .
- Use Case: Ideal for chatbots, content generation, and research applications.
- API Access: Use
model="deepseek-chat"with the OpenAI-compatible API . - Product Page: chat.deepseek.com (interactive demo) .
2. DeepSeek-R1 (DeepSeek-Reasoner): Advanced Reasoning Model
- Description: A specialized model for mathematical reasoning, coding, and logic-intensive tasks. It leverages pure reinforcement learning and is MIT-licensed for open-source use .
- Performance: Competes with OpenAI’s o1 model while offering significantly lower API costs .
- Use Case: Academic research, complex problem-solving, and AI-driven analytics.
- API Access: Set
model="deepseek-reasoner". Pricing: $0.55/million input tokens (cache miss), $2.19/million output tokens . - Technical Report: DeepSeek-R1 GitHub .
3. DeepSeek-Coder-V2: Code-Focused Model
- Description: A 236-billion-parameter model optimized for coding tasks, supporting context lengths up to 128K tokens. It excels at code completion, debugging, and complex algorithm design .
- Use Case: Software development, code automation, and educational tools.
- API Pricing: $0.14/million input tokens and $0.28/million output tokens .
4. Distilled Models (R1-Distill)
- Description: Smaller, efficient models distilled from DeepSeek-R1. Available in 6 variants (e.g., 32B and 70B parameters), these models retain high performance at reduced computational costs .
- Use Case: Edge computing, mobile apps, and cost-sensitive applications.
- Open-Source Access: Model weights and training pipelines are publicly available .
API Documentation and Resources
DeepSeek provides comprehensive, OpenAI-compatible API documentation for seamless integration:
- API Reference: DeepSeek API Docs
- Includes setup guides, authentication details, and code examples for Python, Node.js, and cURL .
- Reasoning Model Guide: DeepSeek-R1 API Guide
- Specialized documentation for optimizing DeepSeek-R1’s reasoning capabilities .
- GitHub Resources:
- Technical reports and distilled model repositories are available on DeepSeek’s GitHub .
Why Choose DeepSeek?
- Cost Efficiency: Up to 90% cheaper than competitors like OpenAI .
- Open-Source Commitment: Full access to model weights and training methodologies .
- Scalability: MoE architecture and distillation techniques enable deployment across diverse hardware .
For developers and enterprises seeking cutting-edge AI with minimal overhead, DeepSeek’s products offer a compelling blend of performance, affordability, and flexibility. Explore the links above to get started!
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