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 Exa
Pricing, pros, cons, and ideal use cases — side by side.
ExaFreemium
A search API built for AI agents rather than humans — structured outputs, token-efficient highlights, and sub-200ms responses.
At a glance
| Baseten | Exa | |
|---|---|---|
| Pricing | PaidUsage-based pricing tied to the compute your deployed models consume. | FreemiumFree trial via the dashboard; usage-based pricing published on the pricing page rather than the homepage. |
| 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 research and enrichment agentsDevelopers replacing scrape-and-parse pipelinesCoding agents needing current documentationAnyone paying too many tokens for web content |
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
Exa
Pros
- Roughly 90% token reduction versus fetching full pages
- Structured JSON output against your own schema
- Sub-180ms latency
- Zero data retention plus SOC 2 Type II and HIPAA coverage
- Used in production by Cursor, Cognition, and HubSpot
Cons
- Usage pricing is not on the homepage — model your volume first
- Another metered dependency in the agent loop
- Index coverage differs from Google; verify recall on your domain
- Overkill if you only need occasional lookups
Which should you choose?
Exa 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; Exa leans more toward teams building research and enrichment agents. Shortlist the one whose strengths line up with your biggest constraint.