Recently, IBM announced the launch of version 3.1 of its open source language model Granite, which brings many important enhancements. The new version of the model has been redesigned with a denser architecture, capable of handling up to 128,000 tokens at once. This update signifies a substantial improvement in Granite's ability to process complex text and tasks. The Granite 3.1 model has been trained on datasets in 12 languages and 116 programming languages, processing a total of 12 trillion tokens.

IBM has officially launched its next-generation open-source large language model, Granite3.1, aiming to secure a leading position in the enterprise AI sector. This series of models features an extended context length of 128K, embedding models, built-in hallucination detection capabilities, and significant performance improvements. IBM claims that the Granite8B Instruct model outperforms its open-source competitors of similar scale, including Meta's Llama3.1, Qwen2.5, and Google's Gemma2.

Red Hat recently released the latest version 1.3 of its enterprise-grade Linux AI platform, RHEL AI, which adds support for IBM's Granite large language model (LLM) and previews support for the Intel Gaudi 3 accelerator. This update brings more opportunities for Red Hat's service partners and system integrators to help enterprises explore and integrate AI applications more effectively. Joe Fernandez, Vice President and General Manager of Red Hat's AI business unit, stated that