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// RUN — FITS
Can the NVIDIA B200 run Xinyuan (心元大模型)?
Yes — here's how fast and up to what context, with real measured numbers.
Xinyuan (心元大模型) on the NVIDIA B200
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 898k | 208.6-248.6 t/s | ~1-1.2 (slow) |
| Q8 | yes | 984k | 417.1-497.1 t/s | ~2.1-2.5 (slow) |
| Q4 | yes | 1021k | 744.9-887.8 t/s | ~3.7-4.4 (slow) |
Estimate (memory-bound). Beyond "max context" the KV cache spills to system RAM offload (depends on your system RAM) and speed drops to the "beyond" figure.
FAQ
Can the NVIDIA B200 run Xinyuan (心元大模型)?▶
Yes. At Q4 it generates ~744.9-887.8 tok/s and fits up to 1021k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~3.7-4.4 tok/s.
How much context fits?▶
At Q4, up to about 1021k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.