Gemini API vs Vertex AI
Two sides of the LLM API decision: model provider and through your cloud. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.
Gemini APIModel providerIn Lovable, ReplitWhich fits you
- You want the strongest general models and the widest ecosystem of examples and integrations
Use it whenYou feed in whole documents, video or audio, or want to start without paying.
Trade-offFree-tier prompts may be used to improve Google's products, so paid tier is the one for user data.
- Gemini and partner models such as Claude on Google Cloud, with its regions, IAM and billing.
Use it whenYou run on Google Cloud or have its credits, and want Gemini with enterprise data terms.
Trade-offMore setup than the Gemini API (a Cloud project, service accounts, regions), for the same models.
At a glance
| Used by | 99 makers' products · 227 open-source projects | 3 makers' products · 59 open-source projects |
|---|---|---|
| Cost at default usageinput tokens 50 million tokens, output tokens 10 million tokens | $28/mo Gemini 3.1 Flash-Lite | — |
| Downloads | 19.2M/wk6.5× vs npm | 3.2M/wk5.7× vs npm |
| Pricing | Free tier with rate limits; pay per token. · paid from Pay per token | Pay per token by model, billed to your Google Cloud account. · paid from Pay per token |
| Free tier | Yes | No |
| Open source | No | No |
What makers say
Makers on using it for LLM API, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.
Powers all agent conversations on Konfide. Fast, cost-effective, handles unlimited concurrent chats. Every user message goes through Gemini. Chose it for speed and quality at scale.
Gemini gives us another strong option for routing complex tasks. Fast response times and competitive pricing mean we can offer our customers more flexibility in how their automations run.
Saturn uses Gemini for structured data extraction from Japanese government filings (EDINET, gBizINFO). Best cost-performance ratio for Japanese language processing at scale.
No maker quote about Vertex AI for LLM API yet.
Loved and watch-outs
Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.
