GTE Large EN v1.5
Alibaba (Tongyi Lab) general text embedding model. The v1.5 release extends the context to 8192 tokens and returns 1024-dim vectors, scoring competitively on MTEB while handling much longer inputs than typical 512-token encoders. A practical open model when documents exceed the usual short-context limit.
GTE Large EN v1.5 is embeddings AI model from huggingface, priced at €0.000 per 1M input tokens with a 8.2K tokens context window.
About this model
Pricing
API Integration
Use our OpenAI-compatible API to integrate GTE Large EN v1.5 into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
const vectors = await rw.run("gte-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("gte-large-en-v1-5", ["Hello", "World"]);
for (const item of res.data) {
console.log(item.embedding.length);
}Frequently asked questions
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