Can the Arc Pro B60 run Qwen3-30B-A3B-Instruct-2507?
Yes. Qwen3-30B-A3B-Instruct-2507 fits the Arc Pro B60's 24 GB at Q4_K_M (about 19.8 GB needed), running at an estimated 99 tok/s. There's room for up to Q5_K_M if you want higher quality.
Every quantization
Qwen3-30B-A3B-Instruct-2507 (30.5B, 3B active) on 24 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 18 GB | 19.8 GB | Fits | ~99 tok/s |
| Q5_K_M | 22 GB | 23.8 GB | Tight | ~81 tok/s |
| Q8_0 | 33 GB | 34.8 GB | Too big | - |
| FP16 | 61 GB | 62.8 GB | Too 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.
Run it
Copy, paste, go
llama-server -hf unsloth/Qwen3-30B-A3B-Instruct-2507-GGUF -ngl 99Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3-30B-A3B-Instruct-2507 details →
Compare
Same model, other hardware - and other models on this card
Qwen3-30B-A3B-Instruct-2507 on other hardware
- RTX 5090~387 tok/s
- RTX 5090 D~387 tok/s
- RTX 6000D~339 tok/s
- RTX 4090~236 tok/s
- Radeon RX 7900 XTX~207 tok/s
- RTX 3090~206 tok/s
- MacBook Pro 16" M4 Max~118 tok/s
- DGX Spark (GB10)~59 tok/s
Also runs on the Arc Pro B60
- GLM-4.7-Flash~101 tok/s
- Qwen3.6 27B~16 tok/s
- Qwen3.8 27B~16 tok/s
- Gemma 4 26B A4B~77 tok/s
- gpt-oss-20b~87 tok/s
- Qwen2.5-Coder-14B-Instruct~29 tok/s
- Qwen3 14B~33 tok/s
- Phi-4~31 tok/s
Frequently asked
Quick answers
Can the Arc Pro B60 run Qwen3-30B-A3B-Instruct-2507?
Yes. Qwen3-30B-A3B-Instruct-2507 fits the Arc Pro B60's 24 GB at Q4_K_M (about 19.8 GB needed), running at an estimated 99 tok/s. There's room for up to Q5_K_M if you want higher quality.
How much VRAM does Qwen3-30B-A3B-Instruct-2507 need?
About 18 GB of weights at Q4_K_M, 33 GB at Q8_0 and 61 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is Qwen3-30B-A3B-Instruct-2507 on the Arc Pro B60?
Roughly 99 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; as a mixture-of-experts model only about 3B parameters are read per token, which is why it is faster than its size suggests.