⚙️ Сбер опубликовал веса и код GigaChat 3.1 Ultra & Lightning под лицензией MIT
Теперь готовые модели можно инсталлировать в собственную инфраструктуру. Флагман на 702B параметров (36B активных) в тестах на reasoning и математику обходит DeepSeek-V3 и Qwen3-235B.
Архитектура использует MoE, MTP и MLA. Для высокой скорости работы предусмотрена облегченная Lightning-версия на 10B параметров. Модели совместимы с популярными стеками: HuggingFace, vLLM, SGLang, llama.cpp. При обучении с нуля команда даже зарепортила критический баг в SGLang.
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