What does Gemini Embedding 001 do?

It converts text into numeric vectors (embeddings) for semantic search, retrieval, clustering and RAG. It does not generate chat text.

What input length does Gemini Embedding 001 support?

Up to 20K tokens per input. Longer documents should be chunked before embedding.

How much does Gemini Embedding 001 cost?

Usage-based pricing: $0.15/M in.

What is Gemini Embedding 001 good for?

Semantic search, retrieval-augmented generation, deduplication, clustering, classification and recommendation over text.

How do I access Gemini Embedding 001 from inside Iran?

Create an account on Hormouz and generate an API key. Hormouz provides stable access from inside Iran via an OpenAI-compatible API.

Google: Gemini Embedding 001: AI model

Gemini Embedding 001 is a Google text-embedding model that maps inputs into dense vectors for semantic search, retrieval and RAG. Up to a 20K-token input, via Hormouz.

Context window:: 20,000 tokens
Input:: $0.15/1M tokens
Output:: $0/1M tokens
Type:: embedding

Embeddings

Gemini Embedding 001 is a Google embedding model that turns text into fixed-length numeric vectors. Those vectors place semantically similar inputs close together, which is the foundation for semantic search, clustering, classification, recommendation and retrieval-augmented generation (RAG). It accepts inputs up to 20K tokens.

Because embeddings are precomputed once and then compared cheaply, this model suits high-volume pipelines: index a corpus, embed each incoming query, and rank documents by vector similarity. It is tuned for multilingual text across domains such as science, law, finance and code.

Pricing is usage-based at $0.15/M in. Gemini Embedding 001 is served through Hormouz behind an OpenAI-compatible API, with stable access from inside Iran.

gemini-embedding-001 provides a unified cutting edge experience across domains, including science, legal, finance, and coding. This embedding model has consistently held a top spot on the Massive Text Embedding Benchmark...

Quickstart

curl https://api.hormouz.net/v1/embeddings \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-embedding-001","input":"The quick brown fox"}'

Specs

Vendor	Google
Type	Embedding
Context window	20,000 tokens
Pricing	$0.15/M in · $0.00/M out
API	embeddings

Code example

cURL

curl https://api.hormouz.net/v1/embeddings \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"google/gemini-embedding-001","input":"The quick brown fox"}'

Python

from openai import OpenAI
client = OpenAI(api_key="ng-YOUR_API_KEY", base_url="https://api.hormouz.net/v1")
resp = client.embeddings.create(model="google/gemini-embedding-001", input="The quick brown fox")
print(resp.data[0].embedding)

JavaScript

import OpenAI from "openai";
const client = new OpenAI({ apiKey: "ng-YOUR_API_KEY", baseURL: "https://api.hormouz.net/v1" });
const resp = await client.embeddings.create({
  model: "google/gemini-embedding-001",
  input: "The quick brown fox",
});
console.log(resp.data[0].embedding);

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FAQ

What does Gemini Embedding 001 do?: It converts text into numeric vectors (embeddings) for semantic search, retrieval, clustering and RAG. It does not generate chat text.
What input length does Gemini Embedding 001 support?: Up to 20K tokens per input. Longer documents should be chunked before embedding.
How much does Gemini Embedding 001 cost?: Usage-based pricing: $0.15/M in.
What is Gemini Embedding 001 good for?: Semantic search, retrieval-augmented generation, deduplication, clustering, classification and recommendation over text.
How do I access Gemini Embedding 001 from inside Iran?: Create an account on Hormouz and generate an API key. Hormouz provides stable access from inside Iran via an OpenAI-compatible API.

Updated 2026-10-13