Granite Embedding Multilingual R2

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0.10BText

granite embedding 97m multilingual r2

Granite-Embedding-97M-Multilingual-R2 is a 97M parameter dense embedding model from the Granite Embeddings collection, designed for multilingual text embeddings. It uses a ModernBERT-based bi-encoder architecture, produces 384-dimensional vectors, and supports context lengths up to 32,768 tokens. The model is released under the Apache-2.0 license and supports 200+ languages, with enhanced support for 52 languages and programming code. It is available with ONNX and OpenVINO formats and is compatible with sentence-transformers, vLLM, and llama.cpp (GGUF).

Model size: 0.10B
Format: FP16 weights
Context: 32,768

Freshness 50 out of 100. Repository age: 178 days old, Apr 20, 2026. Measures age, not quality.

Popularity 66 out of 100. 114,001 downloads in 30 days; 147 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.

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0.31BText

granite embedding 311m multilingual r2

Granite-Embedding-311M-Multilingual-R2 is a 311M-parameter dense embedding model from IBM's Granite Embeddings collection, licensed Apache-2.0. It produces 768-dimensional vectors and supports a context length of up to 32,768 tokens. The model is based on the ModernBERT architecture and supports 200+ languages, with enhanced support for 52 languages and programming code. It is released with ONNX and OpenVINO models and is tagged for sentence-transformers, feature extraction, and multilingual use.

Model size: 0.31B
Format: FP16 weights
Context: 32,768

Freshness 50 out of 100. Repository age: 178 days old, Apr 20, 2026. Measures age, not quality.

Popularity 68 out of 100. 150,966 downloads in 30 days; 143 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.

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