Can I Run / Qwen 3.5 4B / on NVIDIA DGX Spark
Can I Run Qwen 3.5 4B on a NVIDIA DGX Spark?
Yes
Runs at full precision (f32). Zero quality loss.
Model size
4.7B
GPU memory
128GB
Smallest quant
Q3_K_S
Best fit
f32
12 quantizations fit your 128GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| f32BEST | 19.8 GB | 21.3 GB | 1.3 GB | +108.2 GB |
| fp16 | 10.4 GB | 11.9 GB | 0.7 GB | +117.6 GB |
| Q8_0 | 6.0 GB | 7.5 GB | 4.5 GB | +122.0 GB |
| Q6_K | 4.9 GB | 6.4 GB | 3.5 GB | +123.1 GB |
| Q5_K_M | 4.3 GB | 5.8 GB | 3.1 GB | +123.7 GB |
| Q5_K_S | 4.2 GB | 5.7 GB | 3.0 GB | +123.8 GB |
| Q4_1 | 3.9 GB | 5.4 GB | 2.8 GB | +124.1 GB |
| Q4_K_M | 3.9 GB | 5.3 GB | 2.7 GB | +124.2 GB |
| Q4_K_S | 3.7 GB | 5.2 GB | 2.6 GB | +124.3 GB |
| Q4_0 | 3.6 GB | 5.1 GB | 2.6 GB | +124.4 GB |
| Q3_K_M | 3.0 GB | 4.5 GB | 2.3 GB | +125.0 GB |
| Q3_K_S | 2.8 GB | 4.3 GB | 2.1 GB | +125.2 GB |
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Full model details
Qwen 3.5 4B →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
NVIDIA DGX Spark →
Top-ranked open-source models that fit in 128GB.
FAQ
Can the NVIDIA DGX Spark run Qwen 3.5 4B?
Yes. The NVIDIA DGX Spark's 128GB of unified memory is enough to run Qwen 3.5 4B at f32 quantization (19.8GB required).
What's the best quantization to use?
f32 is the highest-precision quantization that fits in your 128GB. It uses about 19.8GB of memory and 21.3GB 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.