Can the DGX Spark (GB10) run Qwen3 14B?

Yes. Qwen3 14B fits the DGX Spark (GB10)'s 128 GB at Q4_K_M (about 9.8 GB needed), running at an estimated 20 tok/s. There's room for up to FP16 if you want higher quality.

VRAM
128 GB
Needs at Q4
9.8 GB
Headroom
118.2 GB
Speed (Q4_K_M)
~20 tok/s

Every quantization

Qwen3 14B (14B) on 128 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M8 GB9.8 GBFits easily~20 tok/s
Q5_K_M10 GB11.8 GBFits easily~16 tok/s
Q8_016 GB17.8 GBFits easily~9.8 tok/s
FP1628 GB29.8 GBFits easily~5.6 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 qwen3:14b
llama-server -hf Qwen/Qwen3-14B-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3 14B details →

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

Qwen3 14B on other hardware

Also runs on the DGX Spark (GB10)

Frequently asked

Quick answers

Can the NVIDIA DGX Spark (GB10) run Qwen3 14B?

Yes. Qwen3 14B fits the DGX Spark (GB10)'s 128 GB at Q4_K_M (about 9.8 GB needed), running at an estimated 20 tok/s. There's room for up to FP16 if you want higher quality.

How much VRAM does Qwen3 14B need?

About 8 GB of weights at Q4_K_M, 16 GB at Q8_0 and 28 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen3 14B on the DGX Spark (GB10)?

Roughly 20 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.