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// RUN — FITS
Can the NVIDIA B200 run Prithvi WxC?
Yes — here's how fast and up to what context, with real measured numbers.
Prithvi WxC on the NVIDIA B200
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 2602k | 1269.6-1513 t/s | ~6.3-7.6 (slow) |
| Q8 | yes | 2637k | 2539.1-3026.1 t/s | ~12.7-15.1 (slow) |
| Q4 | yes | 2653k | 4534.2-5403.7 t/s | ~22.7-27 (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 Prithvi WxC?▶
Yes. At Q4 it generates ~4534.2-5403.7 tok/s and fits up to 2653k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~22.7-27 tok/s.
How much context fits?▶
At Q4, up to about 2653k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.