llmreference
Google AI Studio

Using Gemini Embedding on Google AI Studio

Implementation guide · Gemini Embedding · Google DeepMind

Serverless

Quick Start

  1. 1
    Create an account at Google AI Studio and generate an API key.
  2. 2
    Use the Google AI Studio SDK or REST API to call gemini-embedding-001 — see the documentation for request format.
  3. 3
    You'll be billed $0.15/1M input, Free/1M output tokens.

Code Examples

Install
pip install google-genai
API key
GOOGLE_API_KEY
Model ID
gemini-embedding-001

Use the model name directly, e.g. "gemini-2.0-flash", "gemini-1.5-pro", or "gemini-2.5-pro-preview-05-06".

import os
from google import genai

client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
    model="gemini-embedding-001",
    contents="Hello"
)
print(response.text)

About Google AI Studio

Google AI Studio is a model prototyping environment and API access point for Gemini models, offering an inference playground for developers to test and build AI applications.

Pricing on Google AI Studio

TypePrice (per 1M)
Input tokens$0.15
Output tokensFree

Capabilities

No model capability flags are currently sourced.

About Gemini Embedding

Gemini Embedding is a language model from Google DeepMind focused on text embeddings for retrieval and semantic search. It was released 2023-12-13.