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// RUN — FITS
Can the NVIDIA GeForce RTX 5090 run data2vec (language)?
Yes — here's how fast and up to what context, with real measured numbers.
data2vec (language) on the NVIDIA GeForce RTX 5090
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 405k | 927.6-1105.5 t/s | ~20.7-24.7 (slow) |
| Q8 | yes | 416k | 1855.2-2211 t/s | ~41.4-49.4 (slow) |
| Q4 | yes | 420k | 3312.8-3948.2 t/s | ~73.9-88.1 (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 data2vec (language)?▶
Yes. At Q4 it generates ~3312.8-3948.2 tok/s and fits up to 420k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~73.9-88.1 tok/s.
How much context fits?▶
At Q4, up to about 420k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.