Can I Run Qwen 3 Next 80B A3B on a NVIDIA DGX Spark?
Runs at Q8_0 — near-lossless quality.
4 quantizations fit your 128GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 86.0 GB | 87.5 GB | 85.0 GB | +42.0 GB |
| Q6_K | 66.9 GB | 68.4 GB | 65.9 GB | +61.1 GB |
| Q5_K_M | 57.8 GB | 59.3 GB | 56.8 GB | +70.2 GB |
| Q4_K_M | 49.5 GB | 51.0 GB | 48.5 GB | +78.5 GB |
Try it in the cloud first
Don't want to download Qwen 3 Next 80B A3B 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 Qwen 3 Next 80B A3B?
Yes. The NVIDIA DGX Spark's 128GB of unified memory is enough to run Qwen 3 Next 80B A3B at Q8_0 quantization (86.0GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 128GB. It uses about 86.0GB of memory and 87.5GB 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.