D3
Balance

DeepSeek: DeepSeek V3.1

by deepseek →

DeepSeek-V3.1 is a large hybrid reasoning model featuring 671 billion parameters (with 37 billion active parameters) that uniquely supports both 'thinking' and 'non-thinking' modes via prompt templates. It builds upon the DeepSeek-V3 base, enhancing its capabilities with a two-phase long-context training process to achieve an impressive context window of up to 128K tokens. For efficient inference, it utilizes FP8 microscaling. Users can precisely control the model's reasoning behavior using the `reasoning` `enabled` boolean parameter. This model significantly improves tool use, code generation, and reasoning efficiency, delivering performance comparable to DeepSeek-R1 on challenging benchmarks while offering faster response times. It supports structured tool calling, advanced code agents, and sophisticated search agents, making it an excellent choice for research, complex coding tasks, and agentic workflows. DeepSeek-V3.1 succeeds the DeepSeek V3-0324 model and demonstrates strong performance across a wide array of tasks. Key specifications include an 8K token context window (with 128K available via long-context training), a maximum output of 4K tokens, and competitive pricing at $0.15/$0.75 per 1M input/output tokens. It offers capabilities such as functions, code generation, and streaming, making it a versatile tool for various AI applications.

textreasoningcodehybrid AI
79%Quality
33KContext Window
70%Speed
Category
Economy
✓API access
✓Unified context
✓RAG + Knowledge Base
✓24/7 Support
Try This ModelCompare models

✅ Best For

✓
Code Generation
✓
Complex Reasoning
✓
Mathematical Problems

🚀 Capabilities

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Structured output
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JSON mode
⚡
Functions
⚡
Code Generation
⚡
Streaming

❌ Limitations

✗
No Image Generation
✗
No Internet Access
✗
Censored Content

Specifications

Providerdeepseek
Context Window32,768 tokens
Max Output7,168 tokens
Minimum PlanBalance

Pricing

Input Price$0.1500 / 1M tokens
Output Price$0.7500 / 1M tokens

💡 With PRO subscription, cost is reduced by 20%

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