📺 Sber releases GigaChat-3.1 AI-models with open weights

Sber’s RnD team published GigaChat-3.1-Ultra and Lightning under MIT license on Hugging Face.

Both models are trained from scratch on Sber’s own compute and data, not fine-tuned from existing systems.

Ultra is a 702B MoE model that outperforms DeepSeek-V3-0324 and Qwen3-235B in math and reasoning benchmarks.
Lightning is a compact 10B MoE (1.8B active) that reaches high-level performance on arenas while staying fast and efficient.

The models support FP8 training, long context (up to 256k), and can run from large clusters to local environments.

It is clear that Sber is committed to making AI more accessible to developers by helping independent teams build assistants, copilots, and production systems on an open infrastructure.

📊 @tech