GooglePaidOperational

Gemini Embedding 2 Preview

API model name: gemini-embedding-2-preview

Gemini Embedding 2 Preview is Google's embedding model, served on the Api.Airforce unified API. It is priced at $0.20 per million input tokens and $229.63 per million output tokens. Access it through the OpenAI-compatible API with one key, alongside 100+ other models on Api.Airforce.

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Pricing

Input / 1M tokens

$0.20

Output / 1M tokens

$229.63

Cache read / 1M tokens

$5.74

Official input rate

$0.20

Api.Airforce price vs. the provider's official rate.

Specifications

Provider: Google
Type: embedding model

What is Gemini Embedding 2 Preview used for?

models.detail.useCases.embedding

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Gemini Embedding 2 Preview — frequently asked questions

How much does Gemini Embedding 2 Preview cost?: Gemini Embedding 2 Preview is billed pay-as-you-go at $0.20 per 1M input tokens and $229.63 per 1M output tokens. There is no subscription — you only pay for what you use.
What can Gemini Embedding 2 Preview do?: Gemini Embedding 2 Preview is Google's embedding model, accessible through the Api.Airforce API.
Is Gemini Embedding 2 Preview free to use?: Gemini Embedding 2 Preview is a paid, pay-as-you-go model — no subscription, you are only charged for usage.
How do I use Gemini Embedding 2 Preview via the API?: Gemini Embedding 2 Preview is OpenAI-compatible. Point any OpenAI SDK at https://api.airforce/v1 and pass the model ID gemini-embedding-2-preview with your Api.Airforce API key.
Who makes Gemini Embedding 2 Preview?: Gemini Embedding 2 Preview is Google's embedding model, served through the unified Api.Airforce gateway alongside 100+ other models.

All models·Quickstart·Chat API reference

Use Gemini Embedding 2 Preview via the API

OpenAI-compatible — point any OpenAI SDK at https://api.airforce/v1 and pass gemini-embedding-2-preview as the model.

cURL

curl https://api.airforce/v1/chat/completions \
  -H "Authorization: Bearer $AIRFORCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-embedding-2-preview",
    "messages": [{ "role": "user", "content": "Hello!" }]
  }'

Python

from openai import OpenAI
client = OpenAI(base_url="https://api.airforce/v1", api_key="$AIRFORCE_API_KEY")
r = client.chat.completions.create(
    model="gemini-embedding-2-preview",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(r.choices[0].message.content)

JavaScript

import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.airforce/v1", apiKey: process.env.AIRFORCE_API_KEY });
const r = await client.chat.completions.create({
  model: "gemini-embedding-2-preview",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(r.choices[0].message.content);