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LLMs & Generative AI

Install Gemini 3 Pro API SDK for Python and Node.js with pip and npm

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• 2 min read

Developers who want to tap into Gemini 3 Pro’s language capabilities now have a straightforward path to get started, but the first step isn’t a vague “read the docs.” It’s about pulling the right client library into the environment you already use—whether that’s a Python notebook or a Node.js backend. The API isn’t free‑form; it runs on a usage‑based pricing model, so you’ll be billed for each request you send. Because of that, Google supplies official SDKs that handle authentication, request formatting, and response parsing, sparing you from hand‑crafting HTTP calls.

Installing the correct package means you can focus on building prompts and handling output rather than wrestling with low‑level details. Once the library is in place, the next practical concern is keeping your credentials out of source code, a best practice for any service that charges per call. Below you’ll find the exact commands to add the SDKs to your project and the recommended way to store the required API key.

Choose your preferred language and install the official SDK using following commands: Python: pip install google-genai Node.js/JavaScript: npm install @google/genai Store your API key securely in an environment variable: export GEMINI_API_KEY="your-api-key-here" The Gemini 3 Pro API utilizes a pay-as-you-go model, where your costs are primarily calculated based on the number of tokens consumed for both your input (prompts) and the model's output (responses). The key determinant for the pricing tier is the context window length of your request. Longer context windows, which allow the model to process more information simultaneously (like large documents or long conversation histories), incur a higher rate.

The following rates apply to the gemini-3-pro-preview model via the Gemini API and are measured per one million tokens (1M). The API presents several revolutionary parameters one of which is the thinking level parameter, giving full control over to the requester in a very detailed manner.

Related Topics: #Gemini 3 Pro #Google #SDK #Python #Node.js #pip #npm #GEMINI_API_KEY #tokens #context window

Will developers adopt it? The Gemini 3 Pro SDK is available for Python and Node.js with a single pip or npm command. Install python with pip install google-genai; for JavaScript run npm install @google/genai.

Then set the API key in an environment variable, for example export GEMINI_API_KEY="your-api-key-here". Some users may find the environment‑variable approach convenient, while others might prefer secret‑management tools for added security. The model is described as capable of creation, reasoning, and multimodal understanding, and it adds agentic features that could simplify building intelligent applications.

Yet the article offers no performance benchmarks, so the practical advantage over existing models remains unclear. Moreover, pricing is only hinted at with a “pay‑a” fragment, leaving cost implications uncertain. Developers can start experimenting today, but they should monitor usage limits and billing details once they become fully documented.

In short, the installation steps are straightforward; the broader impact on development workflows will depend on how the promised capabilities translate into real‑world results.

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Common Questions Answered

How do I install the Gemini 3 Pro SDK for Python?

You can install the official Gemini 3 Pro Python SDK by running the command `pip install google-genai` in your terminal. This single pip command pulls the client library and its dependencies, allowing you to start making API calls from a Python notebook or script.

What command should I use to add the Gemini 3 Pro SDK to a Node.js project?

For a Node.js or JavaScript backend, install the SDK with `npm install @google/genai`. This npm command adds the @google/genai package to your project's dependencies, enabling you to import and use the Gemini 3 Pro client in your code.

How should I securely provide my Gemini 3 Pro API key to the SDK?

Store the API key in an environment variable, for example by running `export GEMINI_API_KEY="your-api-key-here"` in your shell before starting your application. Both the Python and Node.js SDKs automatically read this variable, keeping the key out of source code.

What pricing model does the Gemini 3 Pro API use and how are costs calculated?

The Gemini 3 Pro API follows a pay‑as‑you‑go model where you are billed based on the number of tokens processed. Costs are incurred for both input tokens (your prompts) and output tokens (the model's responses), so larger requests result in higher charges.

Can I use secret‑management tools instead of environment variables for the Gemini 3 Pro API key?

Yes, while the article highlights the convenience of setting `GEMINI_API_KEY` as an environment variable, developers can also integrate secret‑management solutions like Vault, AWS Secrets Manager, or GCP Secret Manager for added security. These tools allow the SDK to retrieve the key programmatically without exposing it in plain text.