DeepSeekOpen SourceReasoningCoding
DeepSeek R1
DeepSeek’s reasoning-focused model trained with reinforcement learning for multi-step math, science, and coding problem solving.
Tool calling · Thinking · Coding
Last reviewed: 24 July 2026
Overview
DeepSeek’s reasoning-focused model trained with reinforcement learning for multi-step math, science, and coding problem solving.
Capabilities
- Vision: No
- Audio: No
- Tool calling: Yes
- Thinking: Yes
- MCP: No
- Coding: Yes
- Structured output: Yes
Technical specifications
- Provider
- DeepSeek
- License
- Model License (open weights)
- Context window
- 128K
- Parameters
- Reasoning MoE family
- Architecture
- Reasoning / RL-trained
- Release
- 2025
- Modalities
- Text
- Vision
- No
- Audio
- No
- Tool calling
- Yes
- Thinking
- Yes
- MCP
- No
- Open weights
- Yes
- API
- Yes
- Pricing (input)
- DeepSeek API
- Pricing (output)
- DeepSeek API
Supported modalities
Text
Context window
128K (128,000 tokens)
Pricing
Input: DeepSeek API
Output: DeepSeek API
Availability
API: Yes
Chat UI: Yes
Open weights: Yes
Use cases
- Hard math and science questions
- Competitive programming style tasks
- Chain-of-thought heavy research agents
- Open reasoning baselines
Strengths
- Strong reasoning traces and hard-problem performance
- Open weights for research and self-hosting
- Attractive cost for reasoning workloads
Limitations
- Longer outputs / higher latency when thinking
- Less multimodal than proprietary frontier models
Related guides
Related benchmarks
Related research
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