Baseten vs Beam
A side-by-side comparison of Baseten and Beam, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Baseten | Beam |
|---|---|---|
| Category (differs) | Inference | Infra |
| Pricing | FREEMIUM | FREEMIUM |
| License | Proprietary | Proprietary |
| Deployment | Cloud | Cloud |
| Platforms (differs) | Web, API | CLI, API, Linux |
| Model support (differs) | Multi-model | Model-agnostic |
| Vendor (differs) | Baseten | Beam |
| 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
Beam
Deploy GPU endpoints, sandboxes, and queues from a few lines of Python — open-core runtime (beta9) you can self-host.
- Define GPU workloads in pure Python
- Open-source runtime (beta9)
- Fast cold starts and autoscaling
- Free dev tier with monthly credit
- Smaller ecosystem than hyperscalers
- Python-centric; less polyglot
- Newer platform, maturing tooling
When to pick which
Beam leans on GPU compute as a headline capability; Baseten treats it as secondary.
- GPU compute (primary capability)
They also differ on:
- Platforms
- Web, API · CLI, API, Linux
Their capability lists differ in recorded depth — compare the full lists above before deciding.