"How long until my GPU is ready?" is the question I care about most when I rent one for a short job, and it is the number nobody publishes. So this morning (2026-10-26) I launched single-GPU machines of six types on Runcrate through the API, one after another in one batch, and timed every step until a real CUDA matmul finished. Then I deleted each machine the second it was done.

What I measured

For each machine, seconds since the create call returned:

API running: the instance API reports running and hands out the IP.

First SSH: my script's first successful ssh root@ip echo ok (it retries every 2 s once it has the IP).

First CUDA op: after SSH, install uv , create a venv, uv pip install torch --torch-backend=cu128 , then multiply two 4096x4096 matrices on the GPU and synchronize.

I also read two clocks on the machine itself, because they tell you where the time goes: kernel boot ( uptime -s ) and when ssh.service came up ( systemctl show ssh -p ActiveEnterTimestamp ).

The commands

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