Cohere Embed v3

Custom
Embeddings

Cohere's multilingual embedding model. Supports 100+ languages with separate search and classification modes.

Try Cohere Embed v3

Vector output (1536 dimensions):

-0.58250.51480.1426-0.72500.29920.6492-0.1916-0.5579-0.75130.0210-0.86830.06810.2965-0.34870.34290.49920.1699-0.58010.8672-0.7909-0.2634-0.6913-0.70100.6288... 1512 more
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Pricing

Price per Generation
Per generationFree

API Integration

Use our OpenAI-compatible API to integrate Cohere Embed v3 into your application.

Install
npm install railwail
JavaScript / TypeScript
import railwail from "railwail";

const rw = railwail("YOUR_API_KEY");

const vectors = await rw.run("cohere-embed-v3", "Hello world", { type: "embed" });
console.log(vectors[0].length); // embedding dimensions

// Or use the embed() method for full control
const res = await rw.embed("cohere-embed-v3", ["Hello", "World"]);
for (const item of res.data) {
  console.log(item.embedding.length);
}
Specifications
Provider
xAI
Category
Embeddings
Tags
multilingual
search
Cohere
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