Text multilingual embedding 002 API

Q: What is the Text multilingual embedding 002 model ID?

Use google/text-multilingual-embedding-002 as the model parameter. Requests go to https://api.aimlapi.com/v1/embeddings with your AI/ML API key.

Try this model

Google's multilingual embedding model 002 supports cross-lingual semantic search and similarity across multiple languages.

Modalities: TextText
Input price: $0.025per 1M tokens
Model type: Embeddings
Released: Dec 13, 2025

Text multilingual embedding 002 overview

Text multilingual embedding 002 by Google

Discover Text-multilingual-embedding-002 API, a powerful model for multilingual text embeddings, enhancing NLP applications across languages.

Text multilingual embedding 002 specs

Model ID: google/text-multilingual-embedding-002
Developer: Google
Input: Text
Output: Text
Endpoint: POST https://api.aimlapi.com/v1/embeddings

Basic Information

Model Name: Text-multilingual-embedding-002
Developer/Creator: Google Cloud

Overview

Text-multilingual-embedding-002 is a state-of-the-art model designed to convert textual data into numerical vector representations, capturing the semantic meaning and context of the input text. It is particularly focused on supporting multiple languages, making it suitable for global applications.

Key Features

High-quality semantic embeddings
Fine-tuned for various NLP tasks
Robust against diverse linguistic structures

Intended Use

Sentiment analysis across languages
Content recommendation systems

Language Support

Text-multilingual-embedding-002 supports a wide range of languages, including but not limited to English, Spanish, French, Chinese, and Arabic, making it suitable for global applications.

The model is also perfect for cross-lingual applications for Clinical Documentation and Research. Learn more about this and other models and their applications in Healthcare here.

Architecture

The model is based on the Transformer architecture, which utilizes self-attention mechanisms to process and generate embeddings that capture contextual relationships between words in multiple languages.

Use cases

Search documents in multiple languages using unified vector space.

Enable conversation understanding and intent matching across languages.

Global classification & clustering

Build language-agnostic models for document categorization or cluster analysis.

Text multilingual embedding 002 API pricing

Text multilingual embedding 002 pricing in US dollars
Usage	Price	Unit
Input	$0.025	1M tokens

Prices from the AI/ML API price list, checked on Nov 4, 2026.

How to use the Text multilingual embedding 002 API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/embeddings' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "google/text-multilingual-embedding-002",
  "input": "The quick brown fox jumps over the lazy dog."
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "google/text-multilingual-embedding-002",
    "input": "The quick brown fox jumps over the lazy dog."
}

response = requests.post("https://api.aimlapi.com/v1/embeddings", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/embeddings", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "google/text-multilingual-embedding-002",
    "input": "The quick brown fox jumps over the lazy dog."
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

Text multilingual embedding 002 FAQ

What inputs and outputs does Text multilingual embedding 002 support?

Text multilingual embedding 002 takes text as input and returns embedding.

When was Text multilingual embedding 002 released?

Text multilingual embedding 002 became available on December 13, 2025.

How much does Text multilingual embedding 002 cost?

Text multilingual embedding 002 costs $0.025 per 1M input tokens on AI/ML API, billed as you go with no subscription.

Who created Text multilingual embedding 002?

Text multilingual embedding 002 was built by Google.

How do I call Text multilingual embedding 002 on AI/ML API?

Send a request to https://api.aimlapi.com/v1/embeddings with google/text-multilingual-embedding-002 as the model id.

Is Text multilingual embedding 002 available through a single API key?

Yes. Text multilingual embedding 002 is served through AI/ML API, so the same key and endpoint format used for other models applies.

Does this model support cross-lingual search and similarity matching?

Yes, it is designed for cross-lingual semantic search and similarity across multiple languages.

What category of model is this?

It is an embeddings model that converts text into vector representations.

What is the Text multilingual embedding 002 model ID?

Use google/text-multilingual-embedding-002 as the model parameter. Requests go to https://api.aimlapi.com/v1/embeddings with your AI/ML API key.

Start building with Text multilingual embedding 002

Get API key

Text multilingual embedding 002 API

google/text-multilingual-embedding-002

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/embeddings' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "google/text-multilingual-embedding-002",
  "input": "The quick brown fox jumps over the lazy dog."
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "google/text-multilingual-embedding-002",
    "input": "The quick brown fox jumps over the lazy dog."
}

response = requests.post("https://api.aimlapi.com/v1/embeddings", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/embeddings", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "google/text-multilingual-embedding-002",
    "input": "The quick brown fox jumps over the lazy dog."
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

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Text multilingual embedding 002 API

Text multilingual embedding 002 overview

Text multilingual embedding 002 by Google

Text multilingual embedding 002 specs

Basic Information

Overview

Key Features

Intended Use

Language Support

Architecture

Use cases

Text multilingual embedding 002 API pricing

How to use the Text multilingual embedding 002 API

Build with your agent

1Get your API key

2Make your first request

Text multilingual embedding 002 FAQ

Start building with Text multilingual embedding 002

Text multilingual embedding 002 API

Build with your agent

1Get your API key

2Make your first request

Text multilingual embedding 002 API

Text multilingual embedding 002 overview

Text multilingual embedding 002 by Google

Text multilingual embedding 002 specs

Basic Information

Overview

Key Features

Intended Use

Language Support

Architecture

Use cases

Text multilingual embedding 002 API pricing

How to use the Text multilingual embedding 002 API

Build with your agent

1Get your API key

2Make your first request

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