DeepSeek V4 Pro VRAM Requirements
Developed by DeepSeek
Find out exactly how much VRAM you need to run DeepSeek V4 Pro locally. Calculate the memory footprint of different GGUF quantization variants (like Q4_K_M or Q8_0), estimate your context length KV cache VRAM footprint, and determine if your hardware supports a full GPU VRAM offload or if you will need to rely on slow partial CPU offloading to avoid a CUDA Out of Memory (OOM) error.
Hardware Configuration
Adjust settings to check compatibility with your system in real time.
Available: 14.50 GB
Available: 29.00 GB
This configuration exceeds your system's usable memory capacity. Attempting to run it will cause crashes or freeze your machine.
Requires 870.77 GB total memory (weights: 805.32 GB, context overhead: 0.95 GB, activation overhead: 64.50 GB).
DeepSeek V4 Pro Quantization Formats & VRAM Compatibility
Select a format to set it as active and calculate your system fit dynamically.
| Quant | Weights | KV Cache | Overhead | Total VRAM | Status | Links |
|---|---|---|---|---|---|---|
| Base (Unquantized) | 805.32 GB | 0.95 GB | 64.50 GB | 870.77 GB | Too Large | HF weights |
DeepSeek V4 Pro KV Cache Memory Breakdown
How to Setup and Run DeepSeek V4 Pro Locally
Method A: Ollama (Recommended)
Ollama is the easiest way to run models in the background. First, download it from ollama.com, then execute this terminal command:
ollama run <model-name>Method B: LM Studio (GUI)
If you prefer a full graphical interface with chat UI and local server hosting:
- Download and install LM Studio.
- Search for DeepSeek V4 Pro in the home page search tab.
- Select a quantization level (like Q4_K_M) that fits your VRAM, click download, and load it to chat.
Model Specs
- DeveloperDeepSeek
- Parameter Count1600B
- Base File Size805.3 GB
- AvailabilityAPI & Local
- Input ModalitiesText
- Official SiteVisit site
Standard Benchmark Scores
Commercial API Pricing
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