Can I Run DeepSeek V4 Flash on a NVIDIA DGX Spark?
Runs at full precision (fp16). Zero quality loss.
5 quantizations fit your 128GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 75.0 GB | 76.5 GB | 74.0 GB | +53.0 GB |
| Q8_0 | 40.3 GB | 41.8 GB | 39.3 GB | +87.7 GB |
| Q6_K | 31.5 GB | 33.0 GB | 30.5 GB | +96.5 GB |
| Q5_K_M | 27.3 GB | 28.8 GB | 26.3 GB | +100.7 GB |
| Q4_K_M | 23.4 GB | 24.9 GB | 22.4 GB | +104.6 GB |
Try it in the cloud first
Don't want to download DeepSeek V4 Flash just to try it? Use a hosted API or rent a GPU by the second.
Affiliate links — we earn a commission at no cost to you.
All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 128GB.
FAQ
Can the NVIDIA DGX Spark run DeepSeek V4 Flash?
Yes. The NVIDIA DGX Spark's 128GB of unified memory is enough to run DeepSeek V4 Flash at fp16 quantization (75.0GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 128GB. It uses about 75.0GB of memory and 76.5GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.