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CoreWeave vs Modal

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

Compared from listings verified as of

CoreWeave

Inference

The AI hyperscaler — GPU cloud built for large-scale training and inference.

View CoreWeave

Modal

Inference

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

View Modal

At a glance

Feature comparison of CoreWeave and Modal
AttributeCoreWeaveModal
CategoryInferenceInference
Pricing (differs)PAIDFREEMIUM
LicenseProprietaryProprietary
DeploymentCloudCloud
Platforms (differs)Web, APIAPI, CLI
Model supportModel-agnosticModel-agnostic
Vendor (differs)CoreWeaveModal Labs

The honest brief

CoreWeave

Operates at a scale smaller GPU clouds can't match — first to stand up new NVIDIA generations, with nine of the ten top AI model providers as customers.

  • Frontier-scale GPU capacity
  • First to new NVIDIA generations
  • Managed Kubernetes + observability
  • Contracted by top AI labs
  • Enterprise-oriented; no free tier
  • Less self-serve than smaller GPU clouds
  • Heavy debt-financed expansion

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