Serverless
Hand-reviewed 2026-07-18 · review after 2026-10-18
Setup: low
- Deployment
- Functions, endpoints, task queues and images are defined through Beam's Python SDK and deployed with the Beam CLI. Task queues provide an asynchronous path for long audio and model jobs.
- function platform · synchronous http · asynchronous job · task queue · scheduled job
- Scale to zero
- Serverless applications scale to zero by default. Configured warm time retains a container after work and is billable.
- supported · default
- Billing behavior
- GPU, CPU and RAM are additive. Beam bills application startup, execution and configured warm time, while its pricing documentation says infrastructure spin-up and container-image loading are not charged.
- Startup behavior
- Beam advertises sub-second restore for checkpointed workloads. End-to-end startup still includes application initialization, and enabling checkpoints requires an initial capture and distribution step.
- Setup
- The normal workflow uses a Beam account, Python SDK and CLI. Images and infrastructure are declared in Python, with optional custom base images and no required external registry in the common path.
- Requires: Beam account and token · Python SDK and Beam CLI · Function, endpoint or task-queue definition
- Important constraints
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- CPU and RAM are material additive charges and should be included when comparing Beam with inclusive machine prices.
- Developer-plan GPU concurrency is lower than paid-plan concurrency.