GPU and memory#
min_vram#
Minimum GPU memory per GPU, in GB. Machines with less are never chosen. This is the most important setting: set it from what your model actually needs, not from the largest GPU you know of.
gpu#
Pin a GPU model. Leave it out to let RunCompute choose; pinning usually costs more.
| Model | Memory | Relative speed |
|---|---|---|
L4 |
24 GB | 0.35 |
RTX4090 |
24 GB | 0.55 |
A6000 |
48 GB | 0.50 |
A100 |
80 GB | 1.00 |
H100 |
80 GB | 1.60 |
H200 |
141 GB | 1.90 |
Relative speed is throughput compared with one A100 and is used to turn
work_units into hours.
gpu_count#
GPUs on one machine, 1 to 8. Hours are divided by the count; the hourly price is multiplied by it.
work_units#
How much compute the job needs, in A100-hours. If a run took 3 hours on one
A100, use 3. If you only know the time on another GPU, multiply by that GPU's
relative speed: 10 hours on an RTX 4090 is about 5.5.
The estimate only affects which machine is picked and the quote. Underestimating does not stop a job early; the budget does.