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// RUN — FITS
Can the NVIDIA DGX Spark run ALBERT-xxlarge?
Yes — here's how fast and up to what context, with real measured numbers.
ALBERT-xxlarge on the NVIDIA DGX Spark
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 1728k | 424-505.3 t/s | ~15.5-18.5 (slow) |
| Q8 | yes | 1731k | 848-1010.7 t/s | ~31.1-37 (slow) |
| Q4 | yes | 1733k | 1514.4-1804.8 t/s | ~55.5-66.1 (slow) |
Estimate (memory-bound). Beyond "max context" the KV cache spills to SSD swap and speed drops to the "beyond" figure.
FAQ
Can the NVIDIA DGX Spark run ALBERT-xxlarge?▶
Yes. At Q4 it generates ~1514.4-1804.8 tok/s and fits up to 1733k context; beyond that it spills to SSD swap and slows to ~55.5-66.1 tok/s.
How much context fits?▶
At Q4, up to about 1733k tokens stay in fast memory; longer context spills to SSD swap and throughput collapses.