Baseten vs Lightning AI
A side-by-side comparison of Baseten and Lightning AI, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Baseten | Lightning AI |
|---|---|---|
| Category (differs) | Inference | Infra |
| Pricing | FREEMIUM | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment (differs) | Cloud | Hybrid |
| Platforms (differs) | Web, API | Web, CLI, API |
| Model support (differs) | Multi-model | Model-agnostic |
| Vendor (differs) | Baseten | Lightning AI |
| Capabilities (differs) |
|
|
The honest brief
Baseten
Pairs prebuilt Model APIs with dedicated Truss deployments and scale-to-zero, so you don't pay for idle GPUs.
- Prebuilt Model APIs for Llama, DeepSeek
- Dedicated GPU/CPU deploys for custom models
- Open-source Truss packaging format
- Production-grade observability and autoscaling
- Dedicated GPU rates run pricier than Modal
- Per-replica cost doubles for redundancy
- Engineering effort to package custom models
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
When to pick which
They share capabilities, but each leads with different ones as a headline job:
Baseten is built around Model inference / serving.
- Model inference / serving (primary capability)
Lightning AI is built around GPU compute.
- GPU compute (primary capability)
They also differ on:
- Deployment
- Cloud · Hybrid
- Platforms
- Web, API · Web, CLI, API
Their capability lists differ in recorded depth — compare the full lists above before deciding.