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The Mosaic Research Team at Databricks has unveiled DBRX, a groundbreaking open, general-purpose Large Language Model (LLM) that redefines the benchmarks for open LLMs. DBRX boasts unparalleled performance across a wide array of standard benchmarks, outperforming established models like GPT-3.5 and showing competitive prowess against Gemini 1.0 Pro, especially noted for its proficiency in programming tasks. This model not only advances the frontiers of model efficiency with its fine-grained mixture-of-experts (MoE) architecture, resulting in significantly faster inference times and reduced parameter counts, but it also makes state-of-the-art LLM capabilities accessible to the open community and enterprises.

Its remarkable efficiency in training and inference is further enhanced when deployed on Mosaic AI Model Serving, offering a compelling solution for those seeking to build or enhance their own LLMs. DBRX’s architecture employs a detailed mixture-of-experts framework, boasting 132B total parameters, with a focus on a higher quality of pretraining data and advanced techniques like rotary position encodings and grouped query attention. The model's superior performance is evident across various benchmarks, including programming and mathematics, where it exceeds other specialized models.

DBRX is now available for Databricks customers and is integrated into GenAI-powered products, showcasing impressive early results. The creation of DBRX leveraged Databricks' suite of tools and a collaborative effort across multiple teams, emphasizing the company’s commitment to advancing the field of generative AI and supporting the open-source community. This move not only positions Databricks at the forefront of LLM development but also promises to revolutionize how enterprises and the open community build and deploy AI models, with DBRX serving as a testament to the potential of collaborative innovation in the field.

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