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Can the NVIDIA GeForce RTX 3080 10GB 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 3080 10GB
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 115k | 3252.1-3875.7 t/s | ~171.2-204 (slow) |
| Q8 | yes | 116k | 6504.1-7751.5 t/s | ~342.3-408 (slow) |
| Q4 | yes | 117k | 11614.5-13841.9 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 3080 10GB run Tensor-Transformer(1core)+PN (WT103)?▶
Yes. At Q4 it generates ~11614.5-13841.9 tok/s and fits up to 117k 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 117k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.