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IBM Granite releases two multilingual embedding models built on ModernBERT

By PulseAugur Editorial · [1 sources] ·

IBM's Granite division has released two new multilingual embedding models, one with 97 million parameters and another with 311 million. These models are based on ModernBERT architecture and support over 200 languages, with a context window of 32,000 tokens. They are designed for applications such as retrieval, search, and similarity tasks, and are available with immediate support on Hugging Face's Text Embeddings Inference platform. AI

IMPACT Expands open-source multilingual embedding options, potentially improving performance for search and retrieval tasks.

RANK_REASON Release of new models from a non-frontier lab with open-source support.

Read on X — Hugging Face →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

IBM Granite releases two multilingual embedding models built on ModernBERT

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0 / 100
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Research
Release of new models from a non-frontier lab with open-source support.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, product
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High
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153 days old
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COVERAGE [1]

  1. X — Hugging Face TIER_1 English(EN) · Hugging Face ·

    RT Alvaro Bartolome: IBM Granite just released two multilingual embedding models with 97M and 311M parameters 🤏🏻 ModernBERT-based, 200+ language...

    RT Alvaro Bartolome<br />IBM Granite just released two multilingual embedding models with 97M and 311M parameters 🤏🏻<br /><br />ModernBERT-based, 200+ languages, 32K context, and built for retrieval, search, similarity, and code.<br /><br />And... day-zero support on Text Embeddi…

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