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// RUN — FITS
Can the NVIDIA B200 run DataGemma?
Yes — here's how fast and up to what context, with real measured numbers.
DataGemma on the NVIDIA B200
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 461k | 107.4-127.9 t/s | ~0.5-0.6 (slow) |
| Q8 | yes | 564k | 214.7-255.9 t/s | ~1.1-1.3 (slow) |
| Q4 | yes | 610k | 383.4-456.9 t/s | ~1.9-2.3 (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 DataGemma?▶
Yes. At Q4 it generates ~383.4-456.9 tok/s and fits up to 610k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~1.9-2.3 tok/s.
How much context fits?▶
At Q4, up to about 610k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.