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// RUN — FITS
Can the NVIDIA GeForce RTX 5060 Ti 16GB 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 5060 Ti 16GB
| Quant | Fits? | Max context | Speed | Beyond context |
|---|---|---|---|---|
| FP16 | yes | 199k | 1917-2284.6 t/s | ~171.2-204 (slow) |
| Q8 | yes | 200k | 3834-4569.3 t/s | ~342.3-408 (slow) |
| Q4 | yes | 201k | 6846.4-8159.4 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.
→ All models on the NVIDIA GeForce RTX 5060 Ti 16GB
→ Tensor-Transformer(1core)+PN (WT103) specs
→ Other hardware
FAQ
Can the NVIDIA GeForce RTX 5060 Ti 16GB run Tensor-Transformer(1core)+PN (WT103)?▶
Yes. At Q4 it generates ~6846.4-8159.4 tok/s and fits up to 201k 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 201k tokens stay in fast memory; longer context spills to system RAM offload (depends on your system RAM) and throughput collapses.