BasetenPaid
A platform for deploying and serving machine-learning models in production, with autoscaling, fast cold starts, and GPU infrastructure managed for you.
AI Infrastructure comparison
Baseten vs Weaviate
Pricing, pros, cons, and ideal use cases — side by side.
WeaviateFreemium
An open-source vector database for production semantic search and RAG, available self-hosted or as a managed cloud service.
At a glance
| Baseten | Weaviate | |
|---|---|---|
| Pricing | PaidUsage-based pricing tied to the compute your deployed models consume. | FreemiumOpen-source and free to self-host. Weaviate Cloud is a managed, usage-based service. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Teams deploying custom or fine-tuned modelsEnterprises needing dedicated, autoscaling model servingOrgs that want to avoid managing GPU infrastructure | Teams building production RAG and semantic searchSaaS apps needing multi-tenant data isolationEnterprises wanting self-hosted or managed options |
Pros & cons
Baseten
Pros
- Production model serving without managing GPUs
- Autoscaling with fast cold starts
- Works with open, fine-tuned, and custom models
- Removes most MLOps overhead
Cons
- Unnecessary if you only use hosted frontier APIs
- Compute-based cost grows with traffic
- Still requires model and evaluation expertise
Weaviate
Pros
- Mature open-source vector database
- Hybrid keyword-plus-vector search
- Multi-tenancy for isolating customer data
- Self-hosted or managed cloud
Cons
- Self-hosting carries an operational burden
- Retrieval quality still depends on your tuning
- Another datastore to run and monitor
Which should you choose?
Weaviate is the lighter-weight option (Freemium), while Baseten sits higher on the pricing ladder (Paid). Baseten is built around teams deploying custom or fine-tuned models; Weaviate leans more toward teams building production rag and semantic search. Shortlist the one whose strengths line up with your biggest constraint.