Can the Arc Pro B60 run Qwen3.8 27B?

Yes. Qwen3.8 27B fits the Arc Pro B60's 24 GB at Q4_K_M (about 17.8 GB needed), running at an estimated 16 tok/s. There's room for up to Q5_K_M if you want higher quality.

VRAM
24 GB
Needs at Q4
17.8 GB
Headroom
6.2 GB
Speed (Q4_K_M)
~16 tok/s

Every quantization

Qwen3.8 27B (27.8B) on 24 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M16 GB17.8 GBFits~16 tok/s
Q5_K_M20 GB21.8 GBTight~13 tok/s
Q8_030 GB31.8 GBToo big -
FP1656 GB57.8 GBToo big -

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.

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

Qwen3.8 27B on other hardware

Also runs on the Arc Pro B60

Frequently asked

Quick answers

Can the Arc Pro B60 run Qwen3.8 27B?

Yes. Qwen3.8 27B fits the Arc Pro B60's 24 GB at Q4_K_M (about 17.8 GB needed), running at an estimated 16 tok/s. There's room for up to Q5_K_M if you want higher quality.

How much VRAM does Qwen3.8 27B need?

About 16 GB of weights at Q4_K_M, 30 GB at Q8_0 and 56 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Qwen3.8 27B on the Arc Pro B60?

Roughly 16 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.