Can I Run Yi 1.5 Family on Beelink SER9 (Ryzen AI 9, 32 GB)?

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Written by Jakub Rusinowski · Last updated May 13, 2024

Yes, but it is tight

Yes, but it is tight — Yi 1.5 34B Chat at Q6_K needs about 31 GB of the 32 GB usable on Beelink SER9 (Ryzen AI 9, 32 GB), leaving only ~1 GB before the runtime starts swapping. Expect ~6.5 tok/s (estimated), with room for about 8,192 tokens of context.

Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~6.5 tok/s

Beelink SER9 (Ryzen AI 9, 32 GB) — what it gives a model

Usable memory for models32 GB
Memory bandwidth256 GB/s
Form factorMini PC
Operating systemWindows or Linux
Memory upgradeableYes
Price$859 (lib/data/ai-stations.ts (street price), checked 2026-07-06)

Yi 1.5 Family on Beelink SER9 (Ryzen AI 9, 32 GB): memory by quantization

QuantMemory neededFits 32 GB?Max contextEst. speedDownload
F1671.6 GB✗ No68.8 GB
Q8_039.4 GB✗ No36.6 GB
Q6_K31 GB✓ Yes8K~6.5 tok/s28.2 GB
Q5_K_M27.2 GB✓ Yes16K~7.4 tok/s24.4 GB
Q4_K_M23.6 GB✓ Yes16K~8.6 tok/s20.8 GB
Q3_K_M17.5 GB✓ Yes16K~11.9 tok/s14.7 GB
Q2_K14.1 GB✓ Yes16K~15.1 tok/s11.3 GB

Which Yi 1.5 Family sizes fit

VariantNeeds at Q4_K_MFits?Est. speed
Yi 1.5 34B Chat23.6 GB✓ Fits~8.6 tok/s
Yi 1.5 9B Chat6.9 GB✓ Fits~31.1 tok/s

What to watch out for

Beelink SER9 32 GB limitations

Recommended setup

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

How these numbers are calculated

FAQ

Can I run Yi 1.5 Family on Beelink SER9 (Ryzen AI 9, 32 GB)?

Yes, but it is tight — Yi 1.5 34B Chat at Q6_K needs about 31 GB of the 32 GB usable on Beelink SER9 (Ryzen AI 9, 32 GB), leaving only ~1 GB before the runtime starts swapping. Expect ~6.5 tok/s (estimated), with room for about 8,192 tokens of context.

Which quantization of Yi 1.5 Family should I use on Beelink SER9 (Ryzen AI 9, 32 GB)?

Q6_K — it needs about 31 GB of the 32 GB available, downloads as roughly 28.2 GB, and runs at an estimated 6.5 tokens/sec with up to 8K of context.

What limits Yi 1.5 Family on Beelink SER9 (Ryzen AI 9, 32 GB)?

Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.

Which runtime should I use?

Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving

Other Computers

Other Models on Beelink SER9 (Ryzen AI 9, 32 GB)

Yi 1.5 Family on GPUs

What This Model Is Good At

Model & Tools

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