DeepSeek V4 Pro — Hardware Requirements & GPU Compatibility
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DeepSeek V4 Pro is a 861.6B-parameter open language model from DeepSeek in the DeepSeek family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 517.29 GB of VRAM — see which GPUs and Macs can run it below.
5.5M downloads
4.7K likesSpecifications
- Publisher
- DeepSeek
- Family
- DeepSeek
- Parameters
- 861.6B
- Architecture
- DeepseekV4ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 129,280
- Release Date
- 2026-05-06
- License
- MIT
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HuggingFace
How Much VRAM Does DeepSeek V4 Pro Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 366.5 GB | 380.8 GB | 366.18 GB | 2-bit quantization with K-quant improvements |
| Q3_K_M | 3.90 | 420.4 GB | 434.7 GB | 420.03 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 517.3 GB | 531.6 GB | 516.96 GB | 4-bit medium quantization — most popular sweet spot |
| Q8_0 | 8.00 | 861.9 GB | 876.2 GB | 861.61 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run DeepSeek V4 Pro?
Q4_K_M · 517.3 GBDeepSeek V4 Pro (Q4_K_M) requires 517.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 673+ GB is recommended. Using the full 1049K context window can add up to 14.3 GB, bringing total usage to 531.6 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run DeepSeek V4 Pro?
Q4_K_M · 517.3 GB2 devices with unified memory can run DeepSeek V4 Pro, including NVIDIA DGX H100.
Decent
— Enough memory, may be tightRelated Models
Derivatives (2)
Frequently Asked Questions
- How much VRAM does DeepSeek V4 Pro need?
DeepSeek V4 Pro requires 517.3 GB of VRAM at Q4_K_M, or 861.9 GB at Q8_0. Full 1049K context adds up to 14.3 GB (531.6 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 861.6B × 4.8 bits ÷ 8 = 517 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 14.6 GB (at full 1049K context)
VRAM usage by quantization
Q4_K_M517.3 GBQ4_K_M + full context531.6 GB- Can NVIDIA GeForce RTX 5090 run DeepSeek V4 Pro?
No — DeepSeek V4 Pro requires at least 366.5 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for DeepSeek V4 Pro?
For DeepSeek V4 Pro, Q4_K_M (517.3 GB) offers the best balance of quality and VRAM usage. Q8_0 (861.9 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 366.5 GB.
VRAM requirement by quantization
Q2_K366.5 GBQ3_K_M420.4 GBQ4_K_M ★517.3 GBQ8_0861.9 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek V4 Pro on a Mac?
DeepSeek V4 Pro requires at least 366.5 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run DeepSeek V4 Pro locally?
Yes — DeepSeek V4 Pro can run locally on consumer hardware. At Q4_K_M quantization it needs 517.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of DeepSeek V4 Pro?
At Q4_K_M, the download is about 516.96 GB. The full-precision Q8_0 version is 861.61 GB. The smallest option (Q2_K) is 366.18 GB.
- Which GPUs can run DeepSeek V4 Pro?
No single consumer GPU has enough VRAM to run DeepSeek V4 Pro at Q4_K_M (517.3 GB). Multi-GPU or professional hardware is required.
- Which devices can run DeepSeek V4 Pro?
2 devices with unified memory can run DeepSeek V4 Pro at Q4_K_M (517.3 GB), including NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.