Back to Blog
NLP March 8, 2025 6 min read

Text Embedding Models in 2025: Which to Use for RAG?

Benchmarking OpenAI, Cohere, E5, BGE, and Jina embeddings on retrieval tasks — MTEB scores, cost, latency, and multilingual support for Arabic and French.

MTEB Benchmark Results (2025)

ModelAvg ScoreDimCost
text-embedding-3-large64.63072$0.13/M tokens
Cohere embed-v364.51024$0.10/M tokens
BGE-M363.81024Free
E5-mistral-7b66.64096Free
Jina-embeddings-v365.21024Free

For Multilingual (AR/FR/EN)

BGE-M3 and Jina-v3 have the best multilingual coverage at zero cost.

My Stack

# Free, local, multilingual
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('BAAI/bge-m3')
embeddings = model.encode(texts, normalize_embeddings=True)
EmbeddingsRAGMTEBMultilingualSemantic Search
O

Ossama Elhakki

AI Engineer & ML Systems Builder — Morocco