Docs
Klio Compute docs
Serverless GPUs for Python. Run a function on a GPU with one decorator, deploy endpoints, task queues, schedules and sandboxes, or deploy an open model behind an OpenAI-compatible API. It scales to zero, and you pay per second from prepaid credit.
pip install klio-compute
klio login --browserless
klio gpusFor agents: /llms.txt indexes every page as markdown, and /llms-full.txt has all of them in one file.
- Quick start
Install the Klio Compute SDK, sign in, and run a Python function in the cloud.
- GPUs
Run a function on a GPU, see live GPU prices, fall back between GPU types, and use 2, 4 or 8 GPUs in one container.
- Endpoints
Deploy a function as an HTTPS endpoint that scales to zero when idle and is called with your key.
- Task queues
Queue work for a function that runs it in the background, one task at a time per container.
- Schedules
Run a function on a cron schedule in UTC.
- Sandboxes
Start an isolated container, run commands or code in it, read and write its files, then terminate it.
- Volumes
Keep files such as model weights in a named volume that every container of your workspace can mount.
- Secrets
Store API keys and passwords once, and give them to the functions that need them as environment variables.
- Images
Choose the container image a function runs in: Python packages, shell commands, or your own base image.
- Deploy an OpenAI-compatible model
Deploy an open model with one command and call it with any OpenAI client and your Klio key.
- Coming from Modal
Run a Modal project on Klio Compute by changing its import line; klio migrate --check reports what works first.
- Pricing and billing
Prepaid credit, billed per second; GPU prices follow the market and a running container keeps the price it started at.
- Limits
What Klio Compute supports today: Python versions, GPUs per container, defaults and what isn't available.
- Command line
The klio commands for running, deploying and managing work, and the options agents and scripts need.