Can the DGX Spark (GB10) run Qwen3 32B?

Yes. Qwen3 32B fits the DGX Spark (GB10)'s 128 GB at Q4_K_M (about 20.8 GB needed), running at an estimated 8.3 tok/s. There's room for up to FP16 if you want higher quality.

VRAM
128 GB
Needs at Q4
20.8 GB
Headroom
107.2 GB
Speed (Q4_K_M)
~8.3 tok/s

Every quantization

Qwen3 32B (32B) on 128 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M19 GB20.8 GBFits easily~8.3 tok/s
Q5_K_M23 GB24.8 GBFits easily~6.8 tok/s
Q8_034 GB35.8 GBFits easily~4.6 tok/s
FP1664 GB65.8 GBFits easily~2.5 tok/s

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the DGX Spark (GB10)'s 273.2 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

ollama run qwen3:32b
llama-server -hf Qwen/Qwen3-32B-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3 32B details →

Compare

Same model, other hardware - and other models on this card

Qwen3 32B on other hardware

Also runs on the DGX Spark (GB10)

Frequently asked

Quick answers

Can the NVIDIA DGX Spark (GB10) run Qwen3 32B?

Yes. Qwen3 32B fits the DGX Spark (GB10)'s 128 GB at Q4_K_M (about 20.8 GB needed), running at an estimated 8.3 tok/s. There's room for up to FP16 if you want higher quality.

How much VRAM does Qwen3 32B need?

About 19 GB of weights at Q4_K_M, 34 GB at Q8_0 and 64 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen3 32B on the DGX Spark (GB10)?

Roughly 8.3 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the DGX Spark (GB10)'s 273.2 GB/s memory bandwidth.