DeepSeek V4 Pro — Hardware Requirements & GPU Compatibility
ChatDeepSeek V4 Pro is a 1598.8B-parameter open language model from DeepSeek in the DeepSeek V4 family. It supports a context window of up to 1,048,576 tokens. At Q4_K_M it needs about 959.63 GB of VRAM — see which GPUs and Macs can run it below.
Specifications
- Publisher
- DeepSeek
- Family
- DeepSeek V4
- Parameters
- 1598.8B
- Architecture
- DeepseekV4ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 129,280
- Release Date
- 2026-04-22
- License
- MIT
Get Started
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 | 679.8 GB | 694.1 GB | 679.51 GB | 2-bit quantization with K-quant improvements |
| Q3_K_M | 3.90 | 779.8 GB | 794.1 GB | 779.43 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 959.6 GB | 973.9 GB | 959.30 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 1139.5 GB | 1153.8 GB | 1139.17 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 1319.4 GB | 1333.7 GB | 1319.04 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 1599.2 GB | 1613.5 GB | 1598.84 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 3198.0 GB | 3212.3 GB | 3197.68 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run DeepSeek V4 Pro?
Q4_K_M · 959.6 GBDeepSeek V4 Pro (Q4_K_M) requires 959.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1248+ GB is recommended. Using the full 1049K context window can add up to 14.3 GB, bringing total usage to 973.9 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Where to Download DeepSeek V4 Pro
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does DeepSeek V4 Pro need?
DeepSeek V4 Pro requires 959.6 GB of VRAM at Q4_K_M, or 3198.0 GB at BF16. Full 1049K context adds up to 14.3 GB (973.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1598.8B × 4.8 bits ÷ 8 = 959.3 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_M959.6 GBQ4_K_M + full context973.9 GB- Can NVIDIA GeForce RTX 5090 run DeepSeek V4 Pro?
No — DeepSeek V4 Pro requires at least 679.8 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 (959.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1139.5 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 679.8 GB.
VRAM requirement by quantization
Q2_K679.8 GBQ4_K_M ★959.6 GBQ5_K_M1139.5 GBQ6_K1319.4 GBQ8_01599.2 GBBF163198.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run DeepSeek V4 Pro on a Mac?
DeepSeek V4 Pro requires at least 679.8 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 959.6 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 959.30 GB. The full-precision BF16 version is 3197.68 GB. The smallest option (Q2_K) is 679.51 GB.
- Which GPUs can run DeepSeek V4 Pro?
No single consumer GPU has enough VRAM to run DeepSeek V4 Pro at Q4_K_M (959.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run DeepSeek V4 Pro?
DeepSeek V4 Pro requires at least 959.6 GB at Q4_K_M, which exceeds the unified memory of most consumer devices. A high-memory Mac Studio, Mac Pro, or multi-GPU desktop setup is recommended.