DeepSeek
DeepSeek V4 Pro (1600B parameters) requires approximately 865.4 GB of VRAM with NVFP4 quantization. As a Mixture of Experts model with 49B 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 996 GB of VRAM.
Get started
— copy & paste to run locallyCopy-paste commands to run DeepSeek V4 Pro on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "deepseek-ai/DeepSeek-V4-Pro" \
--hf-file "DeepSeek-V4-Pro-NVFP4.gguf" \
-c 4096 -ngl 99Quick 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 | 624.0 GB | Low | — |
Q3_K_S | 3 | 784.0 GB | Low | — |
NVFP4 | 4 | 896.0 GB | Medium | — |
Q4_K_M | 4 | 976.0 GB | Medium | — |
Q5_K_M | 5 | 1152.0 GB | High | — |
Q6_K | 6 | 1312.0 GB | High | — |
Q8_0 | 8 | 1712.0 GB | Very High | — |
F16 | 16 | 3280.0 GB | Maximum | — |
Quality benchmarks
Coding
Reasoning
Source: vendor-reported · 2026-04-24
Hardware compatibility
Computing compatibility...
Memory breakdown
Frequently asked questions
DeepSeek V4 Pro (1600B parameters) requires approximately 865.4 GB of VRAM with NVFP4 quantization. Lower quantizations like Q4_K_M use less memory but may reduce quality.
The recommended quantization for DeepSeek V4 Pro is NVFP4, which offers the best balance between model quality and memory efficiency. Higher quantizations preserve more quality but require more VRAM.
Yes, DeepSeek V4 Pro is well-suited for reasoning as well as agentic, coding, long-context. It was designed with these use cases in mind.
See also