Gemini
Why Gemini
Gemini is Google's API for building applications on its Gemini family of AI models, supporting text generation, code, images and video. It provides a single developer API and a free tier with generous rate limits for teams exploring the platform before committing to production workloads.
What it does
This is the Gemini Developer API from Google, reached through ai.google.dev, not the Gemini chat app. It gives developers one API for text, code, image and video generation on Google's models, including Imagen for images and Veo for video. Google AI Studio lets you try models and test prompts before you write code. There are also on-device options through Gemini Nano on Android and Chrome's built-in AI features, and the open Gemma models.
Why you would need it
You need it when a product or an internal workflow has to generate, summarise, classify or extract on its own. A person typing into a chat window does not scale. An API call from your code does.
The other reason is choice. Relying on a single model provider is a risk on price, on quality and on outages. Having Gemini as a second option means you can switch a workload when the numbers change.
Where it fits
Gemini sits underneath your product as the model layer. Your application code, or an agent or workflow tool built on top, calls it. It sits beside other providers such as Anthropic's API and does not replace the rest of your stack.
What stands out
- A free tier with no card needed to start, which is handy for testing.
- Pay as you go on the paid tier, with no monthly minimum.
- Text, image and video generation in one API.
- On-device and browser options for mobile and web use cases.
My take
I would use the Gemini API when you want a second model in your toolbox, or when your product already runs on Google Cloud and you want to stay close. The free tier makes it cheap to compare it against your current model on your own prompts.
What I would watch is budgeting. Pricing is per token and varies a lot by model, which is harder to forecast than a flat fee. Free tier usage may also be used by Google to improve its products, so keep customer data out of it. And do not buy this if you need a finished product for a non-technical team. It is a building block.
Verdict
Pick the Gemini API if you build software and want Google's models, with a cheap way to test them. Skip it if you want a ready-made assistant rather than an API.
Notes
Your note
Before you choose
Per-token pricing is hard to budget
You pay by the token, and rates differ sharply per model. Work out cost per task on real prompts before you commit. Published rates are due to rise from January 2027 for most models, so model your costs on the new numbers.
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Free tier data use
The free tier has limits on models and rate, and Google may use that usage to improve its products. Do not send customer or confidential data through it. Move to the paid tier for production.
Model choice takes reading
Price and capability vary across the range. Pick the model per workload instead of defaulting to the biggest one.
Alternatives to compare
Run the same test on Anthropic's API before you standardise. Switching later is easier if your code keeps the model call in one place.