Google: Gemini Embedding 2 Preview: AI model
Gemini Embedding 2 Preview is a Google text-embedding model that maps inputs into dense vectors for semantic search, retrieval and RAG. Up to a 8K-token input, via Hormouz.
- Context window:
- 8,192 tokens
- Input:
- $0.2/1M tokens
- Output:
- $0/1M tokens
- Type:
- embedding
- Embeddings
Gemini Embedding 2 Preview is a Google embedding model that turns text and images 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 8K 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. Its multimodal input lets you embed text and images into a shared space for cross-modal search.
Pricing is usage-based at $0.2/M in. Gemini Embedding 2 Preview is served through Hormouz behind an OpenAI-compatible API, with stable access from inside Iran.
Gemini Embedding 2 Preview is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It...
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-2-preview","input":"The quick brown fox"}'Specs
| Vendor | |
|---|---|
| Type | Embedding |
| Context window | 8,192 tokens |
| Pricing | $0.20/M in · $0.00/M out |
| API | embeddings |
Code example
curl https://api.hormouz.net/v1/embeddings \
-H "Authorization: Bearer ng-YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"google/gemini-embedding-2-preview","input":"The quick brown fox"}'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-2-preview", input="The quick brown fox") print(resp.data[0].embedding)
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-2-preview",
input: "The quick brown fox",
});
console.log(resp.data[0].embedding);Buy the Google: Gemini Embedding 2 Preview API, paid in rial
- Buy credit with an Iranian bank card; no foreign card or account needed.
- One Hormouz key reaches Google: Gemini Embedding 2 Preview and 600+ other models, and you pay only for what you use.
- No VPN and no risk of a banned account; just change the base URL to api.hormouz.net/v1.
Use via Hormouz
Connect to this model and 600+ others with one API key, then see usage down to each request.
Request company accessFAQ
- What does Gemini Embedding 2 Preview do?
- It converts text, images, PDFs and files, audio and video into numeric vectors (embeddings) for semantic search, retrieval, clustering and RAG. It does not generate chat text.
- What input length does Gemini Embedding 2 Preview support?
- Up to 8K tokens per input. Longer documents should be chunked before embedding.
- How much does Gemini Embedding 2 Preview cost?
- Usage-based pricing: $0.2/M in.
- What is Gemini Embedding 2 Preview good for?
- Semantic search, retrieval-augmented generation, deduplication, clustering, classification and recommendation over text and images.
- How do I access Gemini Embedding 2 Preview 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