Name: Voyage Multilingual 2 API
Brand: Anthropic

Overview

What is Voyage Multilingual 2 API?

Voyage Multilingual 2 is an embedding model supporting 30+ languages for cross-lingual semantic search and retrieval.

Technical Specifications
- Supported inputs: Text
- Output: Embedding
- Context window: 32,000 tokens / Max output: —
- Endpoint: /embeddings

Performance Benchmarks
[embed]

Voyage Multilingual 2 API Pricing
- Input: $0.156 / 1M tokens

Where to Use Voyage Multilingual 2

Semantic search
Rank documents by meaning for retrieval and discovery.

RAG pipelines
Ground LLM answers in your own data via vector retrieval.

Code Sample
[embed]

Use cases

Global multilingual search systems are a documented use case for Voyage Multilingual 2, especially when queries and documents are in different languages and a single index is preferred for unified retrieval.

Cross-lingual knowledge base retrieval is another stated use case, with the model described as enabling language-independent retrieval across multilingual document collections.

Retrieval-augmented generation is explicitly documented as a core fit for the model, which is optimized for multilingual retrieval and RAG.

Multilingual content discovery is also listed as an ideal use case, reflecting its role in surfacing relevant results across many languages.

How to use Voyage Multilingual 2 API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to anthropic/voyage-multilingual-2.

import requests

r = requests.post(
    "https://api.aimlapi.com/v1/embeddings",
    headers={"Authorization": "Bearer " + AIMLAPI_KEY},
    json={
      "model": "anthropic/voyage-multilingual-2",
      "input": "The quick brown fox"
    },
)
print(r.json())

const r = 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": "anthropic/voyage-multilingual-2",
    "input": "The quick brown fox"
  }),
});
console.log(await r.json());

curl -X POST https://api.aimlapi.com/v1/embeddings \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"anthropic/voyage-multilingual-2","input":"The quick brown fox"}'

OpenAI-compatible — swap the base URL and it works with your existing SDK.