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Modal vs Replicate

A side-by-side comparison of Modal and Replicate, two Inference tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Modal

Inference

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

View Modal

Replicate

Inference

Run, fine-tune, and deploy thousands of open models via one API.

View Replicate

At a glance

Feature comparison of Modal and Replicate
AttributeModalReplicate
CategoryInferenceInference
PricingFREEMIUMFREEMIUM
LicenseProprietaryProprietary
DeploymentCloudCloud
Platforms (differs)API, CLIWeb, API, CLI
Model support (differs)Model-agnosticMulti-model
Vendor (differs)Modal LabsReplicate

The honest brief

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

Replicate

Any model is a Cog container behind one API billed per second — the low-commitment way to ship a model you didn't train.

  • Image, video, audio, and language models
  • No idle cost, no infra to manage
  • Cog packaging for custom deploys
  • Fine-tuning supported
  • Cold starts on less-popular models
  • Per-second cost adds up at scale
  • Less control than raw GPU rental
Modal detailsReplicate detailsAll Inference apps