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// RUN — FITS
Can the NVIDIA GeForce RTX 5090 run PlasmidGPT?
Yes — here's how fast and up to what context, with real measured numbers.
PlasmidGPT on the NVIDIA GeForce RTX 5090
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 423k | 5946.2-7086.5 t/s | ~132.7-158.2 (slow) |
| Q8 | yes | 425k | 11892.4-14173.1 t/s | ~265.5-316.4 (slow) |
| Q4 | yes | 425k | 21236.4-25309.1 t/s | ~474-564.9 (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 GeForce RTX 5090 run PlasmidGPT?▶
Yes. At Q4 it generates ~21236.4-25309.1 tok/s and fits up to 425k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~474-564.9 tok/s.
How much context fits?▶
At Q4, up to about 425k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.