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Beam vs Modal

A side-by-side comparison of Beam and Modal, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Beam

Infra

On-demand serverless GPU compute for AI, from Python.

View Beam

Modal

Inference

Serverless GPUs. Run training, inference, batch jobs from Python.

View Modal

At a glance

Feature comparison of Beam and Modal
AttributeBeamModal
Category (differs)InfraInference
PricingFREEMIUMFREEMIUM
LicenseProprietaryProprietary
DeploymentCloudCloud
Platforms (differs)CLI, API, LinuxAPI, CLI
Model supportModel-agnosticModel-agnostic
Vendor (differs)BeamModal Labs

The honest brief

Beam

Deploy GPU endpoints, sandboxes, and queues from a few lines of Python — open-core runtime (beta9) you can self-host.

  • Define GPU workloads in pure Python
  • Open-source runtime (beta9)
  • Fast cold starts and autoscaling
  • Free dev tier with monthly credit
  • Smaller ecosystem than hyperscalers
  • Python-centric; less polyglot
  • Newer platform, maturing tooling

Modal

Define GPU infra in Python decorators with 2-4s cold starts — no YAML, Dockerfiles, or managed-stack lock-in.

  • Python-decorator infra, no YAML/Dockerfiles
  • Scale-to-zero, pay only when running
  • Scales to hundreds of GPUs
  • Free monthly starter credits
  • SDK lock-in; migrating means rewriting
  • No managed vLLM/TensorRT setup
  • Costs climb under heavy usage
  • Billing hard to predict
Beam detailsModal details