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HomeCan I run it?Qwen3-14BQwen3-14B on an Arc B580

Yes, but it is tight. Qwen3-14B at Q4_K_M needs about 11.3 GB, and the Intel Arc B580 has 12.0 GB usable at a ~4k context.

Can I run Qwen3-14B on an Arc B580?

Qwen3-14B at Q4_K_M needs about 11.3 GB, and the Intel Arc B580 has 12.0 GB usable. That figure is 12 GB of VRAM on the spec sheet, of which 12.0 GB is usable for weights and cache, at 456 GB/s memory bandwidth. Alibaba’s 14B Qwen3. It sits in the sweet spot for 12–16 GB cards that want more quality than an 8B. These are estimates from our formula, not measured benchmarks.

Quant that fits
Q4_K_M Fits, short context only
Memory needed
11.3 GB at Q4_K_M, ~4k context
Usable VRAM
12.0 GB of 12 GB VRAM
Est. tokens/sec
31–43 estimate

Qwen3-14B · Intel Arc B580 · Everything this machine runs · Q4 vs Q8 vs FP16

Memory at each quant

QuantNeed vs 12.0 GBVerdict
Q4_K_M11.3 GBQ4Tight
Q8_019.0 GBQ8Won’t fit
FP1635.0 GBFP16Won’t fit

Estimated tokens per second

Estimate: 31–43 tokens/sec at Q4_K_M. This is a bandwidth-derived range, not a bench. Efficiency is a 60–85% GPU band from How we calculate.

Context headroom

At Q4_K_M, this machine has headroom out to about 8k tokens under our KV estimate. Longer chats need more memory for the cache. Figures assume an FP16 KV cache.

Context headroom for Qwen3-14B on an Arc B580 at Q4_K_M
ContextKV cache (FP16)Total at Q4_K_MVerdict
4k0.7 GB11.3 GBTight
8k1.3 GB12.0 GBTight
16k2.7 GB13.3 GBWon’t fit
32k5.4 GB16.0 GBWon’t fit
64k10.7 GB21.4 GBWon’t fit
128k21.5 GB32.1 GBWon’t fit

From the model’s config. Try other sizes in the VRAM calculator or see the context length guide.

What to do instead

Other hardware for Qwen3-14B

Other models on an Arc B580

Quick answers

Can I run Qwen3-14B on an Arc B580?
Yes, but it is tight. Qwen3-14B at Q4_K_M needs about 11.3 GB, and the Intel Arc B580 has 12.0 GB usable.
How much VRAM does Qwen3-14B need?
About 11.3 GB at Q4_K_M, 19.0 GB at Q8_0 and 35.0 GB at FP16, estimated for a ~4k context.
How fast is Qwen3-14B on an Arc B580?
Our estimate is 31–43 tokens per second at Q4_K_M. It is not a measured benchmark.
What context length can I use?
At Q4_K_M, our KV estimate supports up to about 8k tokens before the cache pushes the total over usable memory.

New models, and what they need to run

One short email a week: fresh open models with their VRAM numbers, plus hardware worth watching.