DeepSeek: DeepSeek V3.2 Exp
Model Type
Proprietary Model
API access only
Recommended Use Cases
Try DeepSeek V3.2 Exp
An experimental version of DeepSeek-V3.2, serving as an intermediate step toward next-generation architecture (October 2025). V3.2-Exp introduces DeepSeek Sparse Attention while maintaining performance parity with V3.1-Terminus.
Per DeepSeek:
DeepSeek-V3.2-Exp builds upon V3.1-Terminus by introducing DeepSeek Sparse Attention—a sparse attention mechanism designed to explore and validate optimizations for training and inference efficiency in long-context scenarios.
Role in V3.2 Series
V3.2-Exp is a research-oriented release focused on validating the DeepSeek Sparse Attention architecture rather than advancing raw task accuracy. Training configurations were deliberately aligned with V3.1-Terminus to enable direct comparison.
Key Features
- Architecture: 685B MoE with DeepSeek Sparse Attention (DSA)
- Context Window: 128K tokens
- Purpose: Architecture validation and research
- License: MIT
DeepSeek Sparse Attention (DSA)
- Fine-grained sparse attention mechanism
- Substantial improvements in long-context training and inference efficiency
- Maintains virtually identical model output quality