Granite Embedding Multilingual R2: Open Apache 2.0 Multilingual Embeddings with 32K Context — Best Sub-100M Retrieval Quality

Hugging Face Blog · 2 months ago

IBM released two open-source multilingual embedding models built on ModernBERT architecture: a 97-million-parameter compact model and a 311-million-parameter full-size model, both supporting 200+ languages and 32,768-token context windows. The 97M model achieves a 60.3 score on MTEB Multilingual Retrieval, outperforming all other open multilingual embedders under 100M parameters by 9.4 points compared to its nearest competitor. Both models are Apache 2.0 licensed and work as drop-in replacements in frameworks like LangChain and LlamaIndex, enabling 200+ language support with a single model name change.