What is beta9 used for?

beta9 is an open-source runtime for serverless AI workloads that deploys and scales GPU inference, sandboxes, and background jobs from a Python interface. It is a good fit for serving ML models without managing servers and running background AI jobs at scale.

Is beta9 open source?

Yes. beta9 is open source under the AGPL-3.0 licence. Its source code is on GitHub at beam-cloud/beta9 and is written mainly in Go.

Yes. beta9 is open source, so the software itself is free to use. A managed cloud version is also available, with paid plans from $89 per month.

Can I self-host beta9?

Yes. beta9 can be self-hosted on your own server or infrastructure.

What is beta9 an alternative to?

beta9 is an open-source alternative to Modal, RunPod, Replicate and Lambda. Other open-source alternatives to Modal include OpenFaaS.

Is beta9 actively maintained?

Yes. The most recent commit to beta9 was on 2 October 2026. The project has 1.8k stars on GitHub.

beta9: open-source alternative to Modal, RunPod, Replicate

About beta9

Beam, whose open-source engine lives in the beta9 repository, is a fast runtime for serverless AI workloads. It gives developers a Pythonic interface to deploy and scale AI applications without managing infrastructure. The code is written in Go and released under the AGPL-3.0 license, and topics include GPU, LLM inference, autoscaling, and functions as a service.

Features include sub-second container cold starts using a custom runtime, scheduler, and embedded caching, parallel fan-out to hundreds of containers, hot reloading, webhooks and scheduled jobs, scale-to-zero by default, and mounted distributed storage volumes. GPU support runs on the Beam cloud, with cards such as the RTX 4090 and H100 mentioned, or on your own GPUs.

The project can be self-hosted or used through the hosted platform, which requires creating an account. Beam suits machine learning engineers and startups that want to serve models, run batch jobs, or sandbox untrusted code without operating a Kubernetes GPU cluster themselves.

Key features

Serverless GPU inference
Sub-second container cold starts
Scale-to-zero workloads
Parallel fan-out to many containers
Webhooks and scheduled jobs
Volume storage and bring-your-own GPUs

Good fit for

→Serving ML models without managing servers
→Running background AI jobs at scale

Built with: Go
Tags: serverless; gpu; ai-inference; llm; autoscaling; python; go; self-hosted

beta9: questions and answers

What is beta9 used for?: beta9 is an open-source runtime for serverless AI workloads that deploys and scales GPU inference, sandboxes, and background jobs from a Python interface. It is a good fit for serving ML models without managing servers and running background AI jobs at scale.
Is beta9 open source?: Yes. beta9 is open source under the AGPL-3.0 licence. Its source code is on GitHub at beam-cloud/beta9 and is written mainly in Go.
Is beta9 free?: Yes. beta9 is open source, so the software itself is free to use. A managed cloud version is also available, with paid plans from $89 per month.
Can I self-host beta9?: Yes. beta9 can be self-hosted on your own server or infrastructure.
What is beta9 an alternative to?: beta9 is an open-source alternative to Modal, RunPod, Replicate and Lambda. Other open-source alternatives to Modal include OpenFaaS.
Is beta9 actively maintained?: Yes. The most recent commit to beta9 was on 2 October 2026. The project has 1.8k stars on GitHub.