Granite Embedding Multilingual R2
AssessTools
A pair of open multilingual embedding models for retrieval and cross-lingual search.
Why it's here
Placed in Assess: 1 article(s) of evidence from 1 source(s), led by model releases, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 8Hugging Face Blog·5/14/2026model_releaseIBM Granite Releases Multilingual Embedding R2 Models
IBM has released two Apache 2.0 multilingual embedding models based on ModernBERT: a 97M-parameter compact model and a 311M full-size model. The models support 200+ languages, 32K-token context, and code retrieval across nine programming languages, with strong retrieval benchmark results and Matryoshka support for the larger model.