Hugging Face model card
Fields: tags, gated, license, summary, base model, library name, pipeline tag, base model relation
We are excited to announce the official release of DeepSeek-V3.2-Exp, an experimental version of our model. As an intermediate step toward our next-generation architecture, 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.
- Context
- 164K
- Max output
- 66K
- Input
- $0.27
- Output
- $0.41
Recommended use cases
Strengths in this dataset
- 163,840-token context window
- text input
- 19 supported API parameters listed
Limits and caveats
- Provider behavior and pricing can change; verify the linked sources before production use.
Capability
Model-native facts
Model- Reasoning
- Supported
- Open weights
- Unknown
Provider endpoint facts
Provider endpoint- Tool calling
- Supported
- Structured output
- Supported
- Streaming
- Unknown
- Prompt cache
- Unknown
- Batch
- Unknown
- Fine-tuning
- Unknown
DeepSeek V3.2 Exp Provider pricing
Provider endpoint: deepseek/deepseek-v3.2-exp
- Input
- $0.27 per 1M tokens
- Output
- $0.41 per 1M tokens
- Cached input
- Unknown per 1M tokens
- Image output
- Unknown per 1M tokens
Sources and verification
Official model documentation
Fields: model identity
OpenRouter Models API
Fields: identity, description, modalities, context window, maximum output, pricing, supported parameters
Frequently asked questions
Answers are generated from the same sourced model and provider facts shown above.
We are excited to announce the official release of DeepSeek-V3.2-Exp, an experimental version of our model. As an intermediate step toward our next-generation architecture, 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.
Model specifications and prices may vary by provider and change over time. AIToolly displays sources and verification dates so users can confirm critical details before production use.