Written by Jakub Rusinowski · Last updated July 15, 2026
Yes, but it is tight
Yes, but it is tight — 1-bit Bonsai 27B at Q8_0 needs about 31.2 GB of the 32 GB usable on Beelink SER9 (Ryzen AI 9, 32 GB), leaving only ~0.8 GB before the runtime starts swapping. Expect ~6.4 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: low · Recommended quantization: Q8_0 · Estimated speed: ~6.4 tok/s
| Usable memory for models | 32 GB |
| Memory bandwidth | 256 GB/s |
| Form factor | Mini PC |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Price | $859 (lib/data/ai-stations.ts (street price), checked 2026-07-06) |
| Quant | Memory needed | Fits 32 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 56.5 GB | ✗ No | — | — | 54 GB |
| Q8_0 | 31.2 GB | ✓ Yes | 8K | ~6.4 tok/s | 28.7 GB |
| Q6_K | 24.7 GB | ✓ Yes | 32K | ~8.2 tok/s | 22.1 GB |
| Q5_K_M | 21.7 GB | ✓ Yes | 32K | ~9.4 tok/s | 19.1 GB |
| Q4_K_M | 18.8 GB | ✓ Yes | 64K | ~10.9 tok/s | 16.3 GB |
| Q3_K_M | 14.1 GB | ✓ Yes | 64K | ~15 tok/s | 11.5 GB |
| Q2_K | 11.4 GB | ✓ Yes | 64K | ~18.9 tok/s | 8.9 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| 1-bit Bonsai 27B | 18.8 GB | ✓ Fits | ~10.9 tok/s |
| Ternary Bonsai 27B | 18.8 GB | ✓ Fits | ~10.9 tok/s |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, but it is tight — 1-bit Bonsai 27B at Q8_0 needs about 31.2 GB of the 32 GB usable on Beelink SER9 (Ryzen AI 9, 32 GB), leaving only ~0.8 GB before the runtime starts swapping. Expect ~6.4 tok/s (estimated), with room for about 8,192 tokens of context.
Q8_0 — it needs about 31.2 GB of the 32 GB available, downloads as roughly 28.7 GB, and runs at an estimated 6.4 tokens/sec with up to 8K of context.
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
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