ExaFreemium
A search API built for AI agents rather than humans — structured outputs, token-efficient highlights, and sub-200ms responses.
AI Infrastructure comparison
Exa vs Google Vertex AI
Pricing, pros, cons, and ideal use cases — side by side.
Google Vertex AIPaid
Google Cloud's unified AI platform — access to Gemini and partner models, plus tools to build, deploy, and govern AI and agents.
At a glance
| Exa | Google Vertex AI | |
|---|---|---|
| Pricing | FreemiumFree trial via the dashboard; usage-based pricing published on the pricing page rather than the homepage. | PaidUsage-based pricing across model and platform services, billed through Google Cloud. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Teams building research and enrichment agentsDevelopers replacing scrape-and-parse pipelinesCoding agents needing current documentationAnyone paying too many tokens for web content | Enterprises already on Google CloudTeams wanting Gemini under enterprise governanceOrganizations consolidating the AI lifecycle on one platform |
Pros & cons
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
Google Vertex AI
Pros
- Gemini plus a broad Model Garden
- End-to-end build, deploy, evaluate, and govern
- Inside Google Cloud IAM and compliance
- Strong data and analytics integration
Cons
- Large, complex platform surface area
- Most valuable only if you are already on GCP
- Getting value requires real platform investment
Which should you choose?
Exa is the lighter-weight option (Freemium), while Google Vertex AI sits higher on the pricing ladder (Paid). Exa is built around teams building research and enrichment agents; Google Vertex AI leans more toward enterprises already on google cloud. Shortlist the one whose strengths line up with your biggest constraint.