German Abramov
2026
T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground
Dmitrii Stoianov | Danil Taranets | Olga Tsymboi | Ramil Latypov | Almaz Dautov | Vladislav Kruglikov | Surkov Nikita | German Abramov | Pavel Gein | Dmitry Abulkhanov | Mikhail Gashkov | Viktor Zelenkovskiy | Artem Batalov | Aleksandr Medvedev | Anatolii Potapov
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
Dmitrii Stoianov | Danil Taranets | Olga Tsymboi | Ramil Latypov | Almaz Dautov | Vladislav Kruglikov | Surkov Nikita | German Abramov | Pavel Gein | Dmitry Abulkhanov | Mikhail Gashkov | Viktor Zelenkovskiy | Artem Batalov | Aleksandr Medvedev | Anatolii Potapov
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 3: System Demonstrations)
We introduce T-pro 2.0, an open-weight Russian LLM for hybrid reasoning and efficient inference.The model supports direct answering and reasoning-trace generation, using a Cyrillic-dense tokenizer and an adapted EAGLE speculative-decoding pipeline to reduce latency. To enable reproducible and extensible research, we release the model weights, the T-Wix 500k instruction corpus, the T-Math reasoning benchmark, and the EAGLE weights on HuggingFace. These resources allow users to study Russian-language reasoning and to extend or adapt both the model and the inference pipeline. A public web demo exposes reasoning and non-reasoning modes and illustrates the speedups achieved by our inference stack across domains.T-pro 2.0 thus serves as an accessible open system for building and evaluating efficient, practical Russian LLM applications.Demo: https://t-pro2eagle.streamlit.app/https://huggingface.co/collections/t-tech/t-pro-20