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Own GPU vs rented GPU vs hosted API: a comparison you can redo in an afternoon
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Own GPU vs rented GPU vs hosted API: a comparison you can redo in an afternoon

DEV Community: deeplearningΒ·mujinΒ·5 days ago
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15s threshold

I run SD1.5 in fp32 with model offload on a 4GB GTX 1650. About 150 seconds per 512x768 image. That number is the anchor for everything below: change it to your own per-image time and your own hourly rate, and the table recomputes.

1. The table: cost per image, setup time, control over weights

Own card (GTX 1650, 4GB) Rented GPU (per hour) Hosted API (per image)

Cost per image (your_hourly_rate Γ— 150s / 3600) + electricity β€” the card is already sunk rental_price_per_hour Γ— (150s / 3600) price_per_image β€” read it off the pricing page

Setup time One afternoon: driver, CUDA, offload flags, a smoke test that renders one image One afternoon: the same, plus provisioning and a transfer of your weights Minutes: an API key and one request

Control over the weights Total. You pin the checkpoint file. Total, if you upload your own. Otherwise whatever the image ships. Whatever the provider serves today

Two things I logged that matter more than the arithmetic.…

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