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Can the NVIDIA GeForce RTX 4090 run Tensor-Transformer(1core)+PN (WT103)?
Yes — here's how fast and up to what context, with real measured numbers.
Tensor-Transformer(1core)+PN (WT103) on the NVIDIA GeForce RTX 4090
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 311k | 4313.2-5140.4 t/s | ~171.2-204 (slow) |
| Q8 | yes | 313k | 8626.5-10280.9 t/s | ~342.3-408 (slow) |
| Q4 | yes | 313k | 15404.5-18358.7 t/s | ~611.3-728.5 (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.
FAQ
Can the NVIDIA GeForce RTX 4090 run Tensor-Transformer(1core)+PN (WT103)?▶
Yes. At Q4 it generates ~15404.5-18358.7 tok/s and fits up to 313k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~611.3-728.5 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.