Granite Embedding 311M Multilingual R2 Model Summary: Granite Embedding 311M Multilingual R2 is a 311M parameter dense embedding model from the Granite Embeddings collection for high quality multilingual text embeddings. It produces 768 dimensional vectors with a context length of up to 32,768 tokens. The model supports 200+ languages (based on the multilingual pretraining corpus of the underlying encoder), with enhanced support for 52 languages and programming code that receive explicit retrieval pair and cross lingual training. All training data uses permissive, enterprise friendly licenses, plus IBM collected and IBM generated datasets. Granite Embedding 311M Multilingual R2 shows strong performance across multilingual information retrieval benchmarks, code retrieval, long document search, conversational multi turn, and reasoning retrieval tasks. The multilingual R2 model scores 65.2 on Multilingual MTEB Retrieval (18 tasks) — a +13 point improvement over granite embedding 278m multilingual (52.2) — and averages 56.3 across all retrieval benchmarks, representing a +14.5 point gain over the previous generation. It supports Matryoshka dimension reduction, 32k token context, and sh…
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