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
InferenceThe AI hyperscaler — GPU cloud built for large-scale training and inference.
View CoreWeaveAt a glance
| Attribute | CoreWeave | Modal |
|---|---|---|
| Category | Inference | Inference |
| Pricing (differs) | PAID | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment | Cloud | Cloud |
| Platforms (differs) | Web, API | API, CLI |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | CoreWeave | Modal Labs |
| Capabilities (differs) |
|
|
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
When to pick which
Modal leans on Model inference / serving as a headline capability; CoreWeave treats it as secondary.
- Model inference / serving (primary capability)
They also differ on:
- Pricing
- PAID · FREEMIUM
- Platforms
- Web, API · API, CLI
Their capability lists differ in recorded depth — compare the full lists above before deciding.