deepseek-ai · deepseek_v32 · based on deepseek-ai/DeepSeek-V3.2-Exp-Base
DeepSeek-V3.2
DeepSeek-V3.2 by deepseek-ai: a 685.4B-parameter mixture-of-experts open-weight model under the mit license.
2,421,883 downloads · 1,490 likes · Model card · synced 2026-09-19
Specifications
- Parameters
- 685.4B (21.4B active)
- Architecture
- moe · deepseek_v32
- Layers
- 61
- Hidden size
- 7,168
- KV heads · head dim
- 128 · 56
- Vocabulary
- 129,280
- Native dtype
- bfloat16
- Context window
- 163,840 tokens
- Released
- 2025-12-01
- Last modified on Hub
- 2025-12-01
Features & licensing
- License
- mit
- Commercial use
- Yes
- Modalities
- text
- Tool / function calling
- No
- Reasoning mode
- No
- Languages
- EN
- Quantised variants on Hub
- AWQ, GGUF, bitsandbytes
- Pipeline
- text-generation
Task fit
Editorial scores (0–100) used by the recommendation engine.
- Chat70
- RAG / Q&A70
- Code70
- Summarisation70
- Extraction70
- Agents70
Hardware to run DeepSeek-V3.2
Weights need about 1508 GB at FP16, 792 GB at INT8 and 452 GB at INT4. The KV cache adds roughly 1749 MB per 1,000 tokens per request. For a reference workload of 5 requests per second with 1,500 input and 300 output tokens, total GPU memory is around 1253.1 GB.
| Configuration | VRAM | Utilisation | Est. first token | Cloud / month |
|---|
Estimates only. Run an assessment for your own traffic.
Auto-imported from Hugging Face. Architecture, license and feature data are synced from the model repository; the task-fit scores below are provisional defaults until a curator reviews them.