Can the DGX Spark (GB10) run Llama 3.1 8B?

Yes. Llama 3.1 8B fits the DGX Spark (GB10)'s 128 GB at Q4_K_M (about 7.3 GB needed), running at an estimated 29 tok/s. There's room for up to FP16 if you want higher quality.

VRAM
128 GB
Needs at Q4
7.3 GB
Headroom
120.7 GB
Speed (Q4_K_M)
~29 tok/s

Every quantization

Llama 3.1 8B (8B) on 128 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M5.5 GB7.3 GBFits easily~29 tok/s
Q5_K_M7 GB8.8 GBFits easily~22 tok/s
Q8_010 GB11.8 GBFits easily~16 tok/s
FP1616 GB17.8 GBFits easily~9.8 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 llama3.1:8b
llama-server -hf bartowski/Meta-Llama-3.1-8B-Instruct-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Llama 3.1 8B details →

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

Llama 3.1 8B on other hardware

Also runs on the DGX Spark (GB10)

Frequently asked

Quick answers

Can the NVIDIA DGX Spark (GB10) run Llama 3.1 8B?

Yes. Llama 3.1 8B fits the DGX Spark (GB10)'s 128 GB at Q4_K_M (about 7.3 GB needed), running at an estimated 29 tok/s. There's room for up to FP16 if you want higher quality.

How much VRAM does Llama 3.1 8B need?

About 5.5 GB of weights at Q4_K_M, 10 GB at Q8_0 and 16 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Llama 3.1 8B on the DGX Spark (GB10)?

Roughly 29 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.