deepseek-ai/DeepSeek-V3.2
DeepSeek-V3.2 is DeepSeek's frontier open-source model with 685B total parameters and novel DeepSeek Sparse Attention (DSA) that reduces long-context computational cost by 50%. Trained with a scalable RL framework, it achieves performance comparable to GPT-5, earning gold-medal results at the 2025 IMO and IOI. The model includes reasoning and tool-use capabilities through large-scale agentic synthesis.
api_example.sh
Technical Specifications
Model Architecture & Performance
Pricing
Pay-per-use, no commitments
API Reference
Complete parameter documentation
| Parameter | Type | Default | Description |
|---|---|---|---|
| stream | boolean | true | Enable streaming responses for real-time output. |
| temperature | number | 1 | Recommended 1.0 for optimal performance. |
| max_tokens | number | 8192 | Maximum number of tokens to generate. |
| top_p | number | 0.95 | Controls nucleus sampling. |
Explore the full request and response schema in our external API documentation
Performance
Strengths & considerations
| Strengths | Considerations |
|---|---|
| DeepSeek Sparse Attention — 50% compute savings on long contexts GPT-5-class performance on reasoning benchmarks Gold-medal IMO 2025 and IOI 2025 performance 685B MoE with efficient inference Integrated reasoning into tool-use via RL synthesis MIT License — fully open source | 128K max context window Requires H100/H200 class infrastructure for full deployment No official Jinja chat template — custom encoding required Tool calling may need warm-up on cold-start phases |
Use cases
Recommended applications for this model
Enterprise
Platform Integration
Docker Support
Official Docker images for containerized deployments
Kubernetes Ready
Production-grade KBS manifests and Helm charts
SDK Libraries
Official SDKs for Python, Javascript, Go, and Java
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