---
id: "thenlper/gte-large"
also: ["thenlper/gte-large-20251117", "thenlper/gte-large"]
cheapest_list_usd_per_m: "0.01 in, 0.0 out, at deepinfra on openrouter"
cheapest_effective_usd_per_m: "0.0092 in, 0.0 out, at deepinfra/us on openrouter"
context: 512
max_output: 460
input: ["text"]
output: ["embeddings"]
released: "2025-11-18"
api: ["/api/v1/embeddings"]
endpoints: 2
gateways: "openrouter (2)"
no_training: 1
trains: 0
retains_prompts: 0
---
# Thenlper: GTE-Large

The gte-large embedding model converts English sentences, paragraphs and moderate-length documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for information retrieval, semantic textual similarity, reranking and...