BGE Large EN v1.5
BAAI (Beijing Academy of AI) open-weight English embedding model with 335M parameters. Returns 1024-dim vectors and was a top MTEB English retrieval model on release. The v1.5 update improved similarity distribution so it works well without a query instruction prefix for symmetric tasks. A widely used open alternative to hosted embeddings.
BGE Large EN v1.5 is embeddings AI model from huggingface, priced at €0.000 per 1M input tokens with a 512 tokens context window.
About this model
Pricing
API Integration
Use our OpenAI-compatible API to integrate BGE Large EN v1.5 into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
const vectors = await rw.run("bge-large-en-v1-5", "Hello world", { type: "embed" });
console.log(vectors[0].length); // embedding dimensions
// Or use the embed() method for full control
const res = await rw.embed("bge-large-en-v1-5", ["Hello", "World"]);
for (const item of res.data) {
console.log(item.embedding.length);
}Frequently asked questions
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