---
id: "intfloat/multilingual-e5-large"
also: ["intfloat/multilingual-e5-large-20251117", "intfloat/multilingual-e5-large"]
cheapest_list_usd_per_m: "0.01 in, 0.0 out, at deepinfra/fp32 on openrouter"
cheapest_effective_usd_per_m: "0.0099 in, 0.0 out, at deepinfra/fp32 on openrouter"
context: 512
max_output: 460
input: ["text"]
output: ["embeddings"]
released: "2025-11-18"
api: ["/api/v1/embeddings"]
endpoints: 1
gateways: "openrouter (1)"
no_training: 1
trains: 0
retains_prompts: 0
---
# Intfloat: Multilingual-E5-Large

The multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized for multilingual retrieval, cross-language similarity, and...