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// RUN — FITS
Can the NVIDIA B200 run EngGPT2 16B-A3B?
Yes — here's how fast and up to what context, with real measured numbers.
EngGPT2 16B-A3B on the NVIDIA B200
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 546k | 182.5-217.5 t/s | ~0.9-1.1 (slow) |
| Q8 | yes | 607k | 365-435 t/s | ~1.8-2.2 (slow) |
| Q4 | yes | 634k | 651.8-776.8 t/s | ~3.3-3.9 (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 EngGPT2 16B-A3B?▶
Yes. At Q4 it generates ~651.8-776.8 tok/s and fits up to 634k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~3.3-3.9 tok/s.
How much context fits?▶
At Q4, up to about 634k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.