budecosystem/hex-1

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:May 6, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

Hex1 by budecosystem is a 4 billion parameter language model specifically optimized for Indian languages, supporting Hindi, Kannada, Telugu, Tamil, and Malayalam. It is designed to bridge the linguistic AI gap in India, enabling developers to build intelligent systems that understand and respond in native Indian languages. The model delivers best-in-class performance for Indic language tasks on the MMLU benchmark when compared against leading models like Gemma-2B, LLaMA-3.2-3B, and Sarvam-1. Hex1 is open-source and offers a commercial license, making it suitable for a wide range of applications and services.

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Hex1: An Indic LLM for India

Hex1, developed by budecosystem, is a 4 billion parameter language model specifically engineered to address the significant linguistic gap in Generative AI for India. Recognizing that 90% of India's population is not fluent in English, Hex1 aims to make AI accessible in native Indian languages.

Key Capabilities & Features

  • Multilingual Support: In its initial release, Hex1 supports five major Indian languages: Hindi, Kannada, Telugu, Tamil, and Malayalam, with plans for future expansion.
  • Optimized for Indic Languages: Unlike many leading models predominantly trained on English, Hex1 is built to understand and respond proficiently in Indian languages.
  • Strong Performance: Benchmarked against models like Gemma-2B, LLaMA-3.2-3B, and Sarvam-1, Hex1 demonstrates best-in-class performance across its supported languages on the MMLU benchmark.
  • Open-Source with Commercial License: Hex1 is open-source, providing researchers and developers with access, and includes a commercial license, enabling businesses to build applications and services without restrictive usage terms.

When to Use Hex1

  • Developing AI applications for Indian users: Ideal for creating tools and services that need to interact in Hindi, Kannada, Telugu, Tamil, or Malayalam.
  • Research in Indic NLP: Provides a strong base model for further research and fine-tuning on Indian language tasks.
  • Bridging the digital language divide: Suitable for projects aimed at increasing AI accessibility for non-English speaking populations in India.

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