ModernBERT

IBM released two new multilingual embedding models under Apache 2.0: a 97M-parameter compact model scoring 60.3 on MTEB Multilingual Retrieval (highest in its size class) and a 311M full-size model scoring 65.2. Both support 200+ languages with enhanced retrieval for 52 languages, handle 32K-token context (64x increase over predecessors), and include code retrieval across 9 programming languages.

IBM released Granite Embedding 311M Multilingual R2, a 311-million parameter dense embedding model with 32,768-token context length and support for 200+ languages. The model scores 64.0 on Multilingual MTEB Retrieval (18 tasks), an 11.8-point improvement over its predecessor, and ships with ONNX and OpenVINO models for production deployment.