Q.What makes DeepSeek-R1’s architecture unique?
A.DeepSeek R1 uses a MoE system with 37B active/671B total parameters and 128K context support, optimized through pure reinforcement learning without supervised fine-tuning.
D
Deepseek R1
★3
💬11939
💲Free
DeepSeek R1 is an open-source AI model designed for advanced reasoning, offering both online access and local deployment options. It excels in mathematical reasoning, code generation, and multilingual understanding through its MoE architecture and reinforcement learning techniques. With support for up to 128K tokens and WebGPU acceleration, it provides high-performance solutions for research, enterprise applications, and development tasks.
💻
Platform
web
AI modelCodingIn-browser inferenceMathematicsNatural Language ProcessingOpen-sourceReasoning
What is Deepseek R1?
DeepSeek R1 Online is a platform providing access to the DeepSeek R1 AI model, an open-source AI model for advanced reasoning. It offers both free and no-login access. Designed for complex problem-solving, multilingual understanding, and production-grade code generation, it utilizes a Mixture of Experts (MoE) architecture and advanced reinforcement learning techniques to achieve high performance in mathematics, coding, and general reasoning tasks. The platform also provides access to distilled versions of the model for various use cases.
Core Technologies
- Mixture of Experts (MoE) Architecture
- Reinforcement Learning
- WebGPU Acceleration
- OpenAI-Compatible API
- Distilled Model Variants
Key Capabilities
- Advanced Reasoning
- Mathematical Problem Solving
- Code Generation
- Multilingual Understanding
- Local Deployment
- Chain-of-Thought Visualization
Use Cases
- Solving complex mathematical problems
- Generating production-grade code
- Handling multilingual NLP tasks
- Conducting AI research
- Enterprise code development
- Creating mathematical models
Core Benefits
- High performance in reasoning, mathematics, and coding
- Cost-effective compared to OpenAI o1
- Supports long-context handling (up to 128K tokens)
- Open-source and MIT-licensed
- Offers both online access and local deployment options
Key Features
- Access to DeepSeek R1 and V3 models
- WebGPU-accelerated in-browser inference
- OpenAI-compatible API endpoint
- Distilled model variants for commercial use
- Chain-of-Thought visualization
How to Use
- 1Visit the website to chat with DeepSeek R1 directly online.
- 2Use the DeepSeek R1 WEBGPU Online version for browser-based inference with WebGPU acceleration.
- 3Test the model on the website without login or registration.
- 4Access the OpenAI-compatible API for integration into existing workflows.
Frequently Asked Questions
Q.How does DeepSeek R1 compare to OpenAI o1 in pricing?
A.DeepSeek R1 costs 90-95% less: $0.14/million input tokens vs. OpenAI o1's $15, with equivalent reasoning capabilities.
Q.Can I deploy DeepSeek R1 locally?
A.Yes, DeepSeek R1 supports local deployment via vLLM/SGLang and offers 6 distilled models (1.5B-70B parameters) for resource-constrained environments.
Q.What benchmarks prove DeepSeek R1’s performance?
A.Achieves SOTA in MATH-500 (97.3%), Codeforces (96.3% percentile), and AIME 2024 (79.8%), outperforming most commercial models.
Q.Is DeepSeek R1 open source?
A.Yes, DeepSeek R1 is MIT-licensed with full model weights available on GitHub, allowing commercial use and modification.
Pros & Cons (Reserved)
✓ Pros
- Open-source and MIT-licensed
- High performance in reasoning, mathematics, and coding
- Cost-effective compared to OpenAI o1
- Supports long-context handling (up to 128K tokens)
- Offers both online access and local deployment options
✗ Cons
- Requires some technical knowledge to deploy locally
- Performance may vary depending on the chosen model variant
- Fan-made website, not directly affiliated with DeepSeek
Alternatives
No alternatives found.