# Run GPU jobs with RunCompute

Send a training, fine-tuning or batch job as a container image. RunCompute
compares machines from seven providers, runs the job on the one with the
lowest estimated cost to finish, stops it at your budget, and restarts it from
its last checkpoint if the machine is taken away.

You submit and follow jobs from Python, from the `runcompute` command, from the
[console](/console), or over plain HTTP.

> **Preview.** RunCompute is in preview. Jobs run on a simulated scheduler:
> matching, spend, preemptions and checkpoints behave as documented, but no
> real GPU machine is started and your container is not executed yet.

## Get started

1. [Install and sign in](/docs/get-started/authentication/)
2. [Run your first job](/docs/get-started/quickstart/)
3. [Read logs and outputs](/docs/guides/logs-and-outputs/)

## Run your code

- [Train or fine-tune a model](/docs/guides/training/)
- [Describe a job in a file](/docs/get-started/job-files/)
- [Run many experiments at once](/docs/guides/sweeps/)
- [Use RunCompute from CI](/docs/guides/ci/)

## Reference

- [Python client](/docs/reference/python/)
- [Terminal commands](/docs/reference/cli/)
- [HTTP API](/docs/reference/http-api/)
- [All job parameters](/docs/parameters/)
- [Troubleshooting](/docs/reference/errors/)

## For coding agents

A plain-text copy of every page is at [/docs/llms.txt](/docs/llms.txt). The
OpenAPI schema is at [/api/openapi.json](/api/openapi.json).