Baseten vs vLLM
A side-by-side comparison of Baseten and vLLM, two Inference tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
| Attribute | Baseten | vLLM |
|---|---|---|
| Category | Inference | Inference |
| Pricing (differs) | FREEMIUM | FREE |
| License (differs) | Proprietary | Open source |
| Deployment (differs) | Cloud | Self-host |
| Platforms (differs) | Web, API | Linux, CLI, API |
| Model support | Multi-model | Multi-model |
| Vendor (differs) | Baseten | vLLM Project |
| 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
vLLM
PagedAttention pages the KV cache like OS virtual memory — the throughput trick that made it the OSS serving default.
- Serves most Hugging Face transformer models
- High throughput via continuous batching
- Apache-2.0, fully self-hostable
- OpenAI-compatible server
- Huge contributor community
- You manage the GPU infrastructure
- Setup/tuning learning curve
- Less turnkey than hosted APIs
- Optimized mainly for NVIDIA GPUs
When to pick which
Baseten leans on Multi-model access as a headline capability; vLLM treats it as secondary.
- Multi-model access (primary capability)
They also differ on:
- Pricing
- FREEMIUM · FREE
- License
- Proprietary · Open source
- Deployment
- Cloud · Self-host
- Platforms
- Web, API · Linux, CLI, API
Their capability lists differ in recorded depth — compare the full lists above before deciding.