DeepSeek V4 Pro DSpark — Hardware Requirements & GPU Compatibility
Chat
DeepSeek-V4-Pro-DSpark is not a distinct model but the DeepSeek-V4-Pro checkpoint — a 1.6-trillion-parameter mixture-of-experts model — packaged with an additional DSpark speculative-decoding module bolted on for faster inference; DeepSeek's own card lists 49 billion parameters active per token for the underlying DeepSeek-V4-Pro checkpoint. The V4 series introduces a hybrid attention design combining Compressed Sparse Attention and Heavily Compressed Attention for long-context efficiency, Manifold-Constrained Hyper-Connections for training stability, and the Muon optimizer, and was pretrained on more than 32 trillion tokens. It sits alongside a smaller 284B-total/13B-active V4-Flash sibling that shares the same architecture. Given its enormous total size, it requires a multi-GPU server even heavily quantized. Context length is 1,048,576 tokens (1M). It is released under the MIT license, permitting unrestricted commercial and research use, and was published in June 2026.
DeepSeek V4 Pro DSpark runs on a multi-GPU server
Q4_K_M needs ~990.8 GB · about 8× H200 SXM 141 GB
MIT
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run DeepSeek V4 Pro DSpark
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve deepseek-ai/DeepSeek-V4-Pro-DSpark --max-model-len 16384 --tensor-parallel-size 8Size the nodes from the table above
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Rent 8× H200 SXM node · Q4_K_M
- Estimated hourly price
- ~$28.72/hr
- est., whole server
- GPUs
- 8 GPUs
- 1.1 TB of VRAM
How Much VRAM Does DeepSeek V4 Pro DSpark Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 701.8 GB | 702.2 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Runs on 6× H200 SXM 141 GB | |
| 805.0 GB | 805.4 GB | 3-bit medium — 3-bit medium quantization | Runs on 7× H200 SXM 141 GB | |
| 990.6 GB | 991.1 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Runs on 8× H200 SXM 141 GB | |
| 1176.3 GB | 1176.7 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Runs on 7× B200 192 GB | |
| 1362.0 GB | 1362.4 GB | 6-bit, very good — 6-bit quantization, very good quality | Runs on 8× B200 192 GB | |
| 1650.8 GB | 1651.3 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Runs on 3 nodes of 8× H100 SXM | |
| 3301.3 GB | 3301.7 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Runs on 6 nodes of 8× H100 SXM |
Selected Q4_K_M
4-bit medium quantization990.8GBat 16K context
- Weights
- 990.3 GB
- KV cache
- 0.2 GB
- Overhead
- 0.3 GB
Server-class: ~990.8 GB at 16K context · about 8× H200 SXM 141 GB
Which Hardware Can Run DeepSeek V4 Pro DSpark?
Q4_K_M · 990.6 GBDeepSeek V4 Pro DSpark (Q4_K_M) requires 990.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 1288+ GB is recommended. Using the full 1049K context window can add up to 14.3 GB, bringing total usage to 1004.9 GB. No consumer GPU has enough memory.
Needs server-class hardware
DeepSeek V4 Pro DSpark runs on a multi-GPU server · Q4_K_M needs ~990.8 GB
| Hardware | Quant | Memory | Context | Hardware page | |
|---|---|---|---|---|---|
| 8× H200 SXM 141 GB · 1.1 TB | Q4_K_M | 990.8 GB | 1M ctx | H200 SXM → | Q4_K_M · 990.8 GB · 1M ctx |
| 6× B200 192 GB · 1.2 TB | Q4_K_M | 990.8 GB | 1M ctx | B200 → | Q4_K_M · 990.8 GB · 1M ctx |
By VRAM tier · typical GPUs and Macs at Q4_K_M
Consumer GPUs (up to 32 GB) and Macs up to 512 GB: too small for this model (needs ≥ 702 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
Alternatives to DeepSeek V4 Pro DSpark
DeepSeek V4 family · 12 models →Similar models
2| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| LongCat 2.0Meituan | — | 3917.9 GB | —needs > 24 GB | same size |
| Nex N2.5 Maxnex-agi | — | 3202.1 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- DeepSeek
- Family
- DeepSeek V4
- Parameters
- 1650.5B
- Active parameters
- 102B per token
- Architecture
- DeepseekV4ForCausalLM
- Context Length
- 1,048,576 tokens
- Vocabulary Size
- 129,280
- Release Date
- 2026-06-27
- License
- MIT
Frequently Asked Questions
How much VRAM does DeepSeek V4 Pro DSpark need?
DeepSeek V4 Pro DSpark requires 990.6 GB of VRAM at Q4_K_M, or 3301.3 GB at BF16. Full 1049K context adds up to 14.3 GB (1004.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1650.5B × 4.8 bits ÷ 8 = 990.3 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 14.6 GB (at full 1049K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run DeepSeek V4 Pro DSpark?
No — DeepSeek V4 Pro DSpark requires at least 701.8 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 DSpark?
For DeepSeek V4 Pro DSpark, Q4_K_M (990.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (1176.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 701.8 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run DeepSeek V4 Pro DSpark on a Mac?
DeepSeek V4 Pro DSpark requires at least 701.8 GB at Q2_K. None of the 146 Macs we list has that much usable memory (the largest has 508.5 GB after macOS overhead).
Can I run DeepSeek V4 Pro DSpark locally?
Yes — DeepSeek V4 Pro DSpark can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
What's the download size of DeepSeek V4 Pro DSpark?
At Q4_K_M, the download is about 990.30 GB. The full-precision BF16 version is 3301.00 GB. The smallest option (Q2_K) is 701.46 GB.
Which GPUs can run DeepSeek V4 Pro DSpark?
No single consumer GPU has enough VRAM to run DeepSeek V4 Pro DSpark at Q4_K_M (990.6 GB). Multi-GPU or professional hardware is required.
Which devices can run DeepSeek V4 Pro DSpark?
DeepSeek V4 Pro DSpark requires at least 990.6 GB at Q4_K_M, which exceeds the usable memory of every unified-memory device we list (the largest has 508.5 GB).