Modal vs Vast.ai
A side-by-side comparison of Modal and Vast.ai, two Inference tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Modal | Vast.ai |
|---|---|---|
| Category | Inference | Inference |
| Pricing (differs) | FREEMIUM | PAID |
| License | Proprietary | Proprietary |
| Deployment | Cloud | Cloud |
| Platforms (differs) | API, CLI | Web, CLI, API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | Modal Labs | Vast.ai |
| Capabilities (differs) |
|
|
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
Vast.ai
Marketplace pricing: independent hosts compete, so GPUs (incl. H100s) often run well below first-party clouds like AWS or GCP.
- Often the cheapest GPUs via marketplace
- Per-second billing, $5 minimum
- On-demand, spot, and reserved options
- Large catalog of GPU types
- Host quality and reliability vary
- Not a managed inference platform
- Interruptible instances can be reclaimed
When to pick which
Modal leans on Model inference / serving as a headline capability; Vast.ai treats it as secondary.
- Model inference / serving (primary capability)
They also differ on:
- Pricing
- FREEMIUM · PAID
- Platforms
- API, CLI · Web, CLI, API
Their capability lists differ in recorded depth — compare the full lists above before deciding.