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// RUN — FITS
Can the NVIDIA B200 run MADLAD-400 10B?
Yes — here's how fast and up to what context, with real measured numbers.
MADLAD-400 10B on the NVIDIA B200
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 938k | 272.9-325.2 t/s | ~1.4-1.6 (slow) |
| Q8 | yes | 1004k | 545.8-650.5 t/s | ~2.7-3.3 (slow) |
| Q4 | yes | 1032k | 974.6-1161.5 t/s | ~4.9-5.8 (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 MADLAD-400 10B?▶
Yes. At Q4 it generates ~974.6-1161.5 tok/s and fits up to 1032k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~4.9-5.8 tok/s.
How much context fits?▶
At Q4, up to about 1032k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.