🔌
New: connect Claude & other AIs to GenAIList over MCP — research the catalog and contribute to the shared knowledge base. Learn how →
// RUN — FITS
Can the NVIDIA DGX Spark run data2vec (language)?
Yes — here's how fast and up to what context, with real measured numbers.
data2vec (language) on the NVIDIA DGX Spark
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 1713k | 141.3-168.4 t/s | ~5.2-6.2 (slow) |
| Q8 | yes | 1724k | 282.6-336.8 t/s | ~10.4-12.3 (slow) |
| Q4 | yes | 1729k | 504.7-601.5 t/s | ~18.5-22 (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 data2vec (language)?▶
Yes. At Q4 it generates ~504.7-601.5 tok/s and fits up to 1729k context; beyond that it spills to SSD swap and slows to ~18.5-22 tok/s.
How much context fits?▶
At Q4, up to about 1729k tokens stay in fast memory; longer context spills to SSD swap and throughput collapses.