2025/06/11 by GigaChat Team, Evgenii Kosarev, Valentin, Mamedov +62 · 5 citations
Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Big Data and Digital Economy #Computation and Language (cs.CL) #Computational and Text Analysis Methods #FOS: Computer and information sciences #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2506.09440
openalex publication_date 2025/06/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Generative large language models (LLMs) have become crucial for modern NLP research and applications across various languages. However, the development of foundational models specifically tailored to the Russian language has been limited, primarily due to the significant computational resources required. This paper introduces the GigaChat family of Russian LLMs, available in various sizes, including base models and instruction-tuned versions. We provide a detailed report on the model architecture, pre-training process, and experiments to guide design choices. In addition, we evaluate their performance on Russian and English benchmarks and compare GigaChat with multilingual analogs. The paper presents a system demonstration of the top-performing models accessible via an API, a Telegram bot, and a Web interface. Furthermore, we have released three open GigaChat models in open-source (https://huggingface.co/ai-sage), aiming to expand NLP research opportunities and support the development of industrial solutions for the Russian language.