// RUN โ€” FITS

Can the NVIDIA GeForce RTX 3090 run Very Deep VAEs (ImageNet-64)?

Yes โ€” here's how fast and up to what context, with real measured numbers.

Very Deep VAEs (ImageNet-64) on the NVIDIA GeForce RTX 3090

QuantFits?Max contextSpeedBeyond context
FP16 yes 310k 2733.1-3257.3 t/s ~116.8-139.2 (slow)
Q8 yes 312k 5466.2-6514.6 t/s ~233.6-278.4 (slow)
Q4 yes 313k 9761.1-11633.1 t/s ~417.1-497.1 (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 Very Deep VAEs (ImageNet-64)?โ–ถ

Yes. At Q4 it generates ~9761.1-11633.1 tok/s and fits up to 313k context; beyond that it spills to system RAM offload (depends on your system RAM) and slows to ~417.1-497.1 tok/s.

How much context fits?โ–ถ

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.