Sber Releases GigaChat 3.5 Ultra: 432B Open-Source MoE Flagship
Sber
Sber released GigaChat 3.5 Ultra on July 6: a 432B Mixture-of-Experts model built on a proprietary linear-attention architecture. The model is ~38% smaller than the prior 700B GigaChat 3.1 Ultra, generates long texts up to 4× faster, and approaches DeepSeek 3.2 on coding, math, and multi-step reasoning benchmarks. Available free in the GigaChat app and released as open source on Hugging Face and GitVerse.
Why it matters
One of the largest models with linear attention released as open source; 38% parameter reduction while gaining on benchmarks represents a meaningful efficiency leap for Russian-language enterprise and developer use cases.
Importance: 4/5
Open-source flagship from major Russian lab with novel linear-attention architecture at scale; 5 independent confirmations.