Run

compute run <file.py>::<function> --gpu <sku> [options]

Example:

compute run simple_mlp.py::train --gpu H100-SXM --wait --yes

--gpu H100 is an alias for H100-SXM. --gpu MI300X is the AMD SKU (stock can be tight).

Flags

Flag	Meaning
`--gpu`	SKU. Required unless the `@app.function` decorator already set one.
`--provider`	Optional pin (`runpod`, `hotaisle`). Usually omit.
`--wait`	Stream until terminal; print JSON result. Default is detach after create.
`--timeout`	Function timeout in seconds. Default 600 (10 minutes).
`--args`	JSON object for function kwargs.
`--dry-run`	Print the upload plan. No upload, no machine.
`--yes`	Skip interactive confirmation.
`--json`	(global) machine-readable envelope.

compute run --help is the live flag list.

What happens

The CLI packages the target file (and what it imports from the project).
The API enqueues a run if admission and credit allow it.
A worker provisions a new machine, installs the image, runs the function, streams logs, then terminates the machine.
You get a JSON return value, a receipt, and an empty compute machines list.

Provider vs SKU

You pick a GPU name. Compute picks the provider unless you pass --provider. You do not pick a region or an instance template.

Detached vs wait

# prints run_id and exits
compute run train.py::main --gpu H100-SXM --yes

# later
compute runs status <run_id>
compute logs <run_id> -f
compute runs result <run_id>
compute runs receipt <run_id>

Or do it in one shot with --wait.

Inspect

compute runs list
compute runs status <run_id>
compute runs result <run_id>
compute runs receipt <run_id>

result is the function return value. receipt is billed minutes and the platform fee (see Billing).

Overview

Get started

CLI

Reference

Flags

What happens

Provider vs SKU

Detached vs wait

Inspect

​Flags

​What happens

​Provider vs SKU

​Detached vs wait

​Inspect

Flags

What happens

Provider vs SKU

Detached vs wait

Inspect