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// RUN — FITS
Can the FuriosaAI RNGD run Transformer (Adaptive Input Embeddings) WT103?
Yes — here's how fast and up to what context, with real measured numbers.
Transformer (Adaptive Input Embeddings) WT103 on the FuriosaAI RNGD
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 643k | 1973.7-2398.8 t/s | ~52.6-64 (slow) |
| Q8 | yes | 647k | 3947.4-4797.6 t/s | ~105.3-127.9 (slow) |
| Q4 | yes | 649k | 7048.9-8567.1 t/s | ~188-228.5 (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.
→ All models on the FuriosaAI RNGD
→ Transformer (Adaptive Input Embeddings) WT103 specs
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FAQ
Can the FuriosaAI RNGD run Transformer (Adaptive Input Embeddings) WT103?▶
Yes. At Q4 it generates ~7048.9-8567.1 tok/s and fits up to 649k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~188-228.5 tok/s.
How much context fits?▶
At Q4, up to about 649k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.