Can the Arc Pro B60 run NVIDIA Nemotron 3 Nano 4B?

Yes. NVIDIA Nemotron 3 Nano 4B fits the Arc Pro B60's 24 GB at Q4_K_M (about 3.8 GB needed), running at an estimated 131 tok/s. There's room for up to FP16 if you want higher quality.

VRAM
24 GB
Needs at Q4
3.8 GB
Headroom
20.2 GB
Speed (Q4_K_M)
~131 tok/s

Every quantization

NVIDIA Nemotron 3 Nano 4B (4B) on 24 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M2 GB3.8 GBFits easily~131 tok/s
Q5_K_M3 GB4.8 GBFits easily~87 tok/s
Q8_04 GB5.8 GBFits easily~65 tok/s
FP168 GB9.8 GBFits easily~33 tok/s

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the Arc Pro B60's 456 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.

Run it

Copy, paste, go

llama-server -hf mradermacher/NVIDIA-Nemotron-3-Nano-4B-BF16-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full NVIDIA Nemotron 3 Nano 4B details →

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

NVIDIA Nemotron 3 Nano 4B on other hardware

Also runs on the Arc Pro B60

Frequently asked

Quick answers

Can the Arc Pro B60 run NVIDIA Nemotron 3 Nano 4B?

Yes. NVIDIA Nemotron 3 Nano 4B fits the Arc Pro B60's 24 GB at Q4_K_M (about 3.8 GB needed), running at an estimated 131 tok/s. There's room for up to FP16 if you want higher quality.

How much VRAM does NVIDIA Nemotron 3 Nano 4B need?

About 2 GB of weights at Q4_K_M, 4 GB at Q8_0 and 8 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is NVIDIA Nemotron 3 Nano 4B on the Arc Pro B60?

Roughly 131 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the Arc Pro B60's 456 GB/s memory bandwidth.