Lightning AI vs Modal
A side-by-side comparison of Lightning AI and Modal, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Lightning AI | Modal |
|---|---|---|
| Category (differs) | Infra | Inference |
| Pricing | FREEMIUM | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment (differs) | Hybrid | Cloud |
| Platforms (differs) | Web, CLI, API | API, CLI |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Lightning AI | Modal Labs |
The honest brief
Lightning AI
From the PyTorch Lightning team — Studios are persistent GPU workspaces you pause and resume, not throwaway notebooks.
- Pause/resume persistent GPU Studios
- Code, train, serve, build agents in one place
- Bring-your-own-cloud for enterprise
- Monthly free GPU credits
- Pay-as-you-go can add up
- Tied to its Studio environment
- Less raw control than bare cloud
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