DeepSeek
DeepSeek V3.2 (671B parameters) requires approximately 411.6 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 37B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 474 GB of VRAM.
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— copy & paste to run locallyCopy-paste commands to run DeepSeek V3.2 on your machine.
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ollama run deepseek-v3.2Quick specs
About this model
Related models
Quantization options
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 261.7 GB | Low | — |
Q3_K_S | 3 | 328.8 GB | Low | — |
NVFP4 | 4 | 375.8 GB | Medium | — |
Q4_K_M | 4 | 409.3 GB | Medium | — |
Q5_K_M | 5 | 483.1 GB | High | — |
Q6_K | 6 | 550.2 GB | High | — |
Q8_0 | 8 | 718.0 GB | Very High | — |
F16 | 16 | 1375.6 GB | Maximum | — |
Quality benchmarks
Coding
Reasoning
Source: official · 2025-12-01
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
DeepSeek V3.2 (671B parameters) requires approximately 411.6 GB of VRAM with Q4_K_M quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
The recommended quantization for DeepSeek V3.2 is Q4_K_M, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
Yes, DeepSeek V3.2 is well-suited for chat as well as reasoning, coding, agentic. It was designed with these use cases in mind.
See also