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Can the NVIDIA GeForce RTX 3090 run DEQ-Transformer (Post-LN) + Jacobian Regularisation?
Yes — here's how fast and up to what context, with real measured numbers.
DEQ-Transformer (Post-LN) + Jacobian Regularisation on the NVIDIA GeForce RTX 3090
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 311k | 3486.1-4154.7 t/s | ~149-177.6 (slow) |
| Q8 | yes | 313k | 6972.2-8309.4 t/s | ~298-355.1 (slow) |
| Q4 | yes | 313k | 12450.4-14838.2 t/s | ~532.1-634.1 (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 3090 run DEQ-Transformer (Post-LN) + Jacobian Regularisation?▶
Yes. At Q4 it generates ~12450.4-14838.2 tok/s and fits up to 313k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~532.1-634.1 tok/s.
How much context fits?▶
At Q4, up to about 313k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.