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// RUN — FITS
Can the NVIDIA RTX PRO 6000 Blackwell run Pythia-160m?
Yes — here's how fast and up to what context, with real measured numbers.
Pythia-160m on the NVIDIA RTX PRO 6000 Blackwell
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 1320k | 4088-4872 t/s | ~91.3-108.8 (slow) |
| Q8 | yes | 1322k | 8176-9744 t/s | ~182.5-217.5 (slow) |
| Q4 | yes | 1323k | 14600-17400 t/s | ~325.9-388.4 (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 RTX PRO 6000 Blackwell run Pythia-160m?▶
Yes. At Q4 it generates ~14600-17400 tok/s and fits up to 1323k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~325.9-388.4 tok/s.
How much context fits?▶
At Q4, up to about 1323k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.