This is a simplified guide to an AI model called Deepseek-R1 maintained by Deepseek-Ai. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.
Model Overview
deepseek-r1 represents a major advancement in AI reasoning capabilities, trained through reinforcement learning to match OpenAI's o1 performance across math, code and reasoning tasks. The model builds on research from related models like DeepSeek R1 Distill Qwen 32B and DeepSeek R1 Distill Qwen 14B, developed by deepseek-ai. The base model uses a mixture-of-experts architecture with 671B total parameters but only 37B activated during inference.
Model Inputs and Outputs
The model accepts text prompts and generates responses with up to 32,768 tokens. It works best with clear, direct instructions and mathematical problems that require step-by-step reasoning.
Inputs
- Prompt: Text input describing the task or question
- Temperature: Controls randomness in generation (0.1-1.0, default 0.1)
- Max Tokens: Maximum length of generated response (default 20,480)
- Presence/Frequency Penalties: Fine-tune generation behavior
Outputs
- Text Response: Generated answers with step-by-step reasoning
- Reasoning Chains: Detailed explanations showing work for complex problems
- Verification Steps: Self-checking of mathematical solutions
Capabilities
The model excels at mathematical reason...
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