Russian Sovereign AI Resilience & Autonomy Simulator | AKI Platform

Q: What are the top Russian AI foundation models in 2026?

The premier Russian foundation models in 2026 are YandexGPT 4 (96.4/100 MMLU-RU score by Yandex), GigaChat MAX (95.8/100 by Sber AI), Kandinsky 3.1 (diffusion vision transformer by Sber/AIRI), and YaFSDP (open-source training optimizer by Yandex).

Q: What are the most powerful supercomputers in Russia?

The fastest sovereign supercomputer in Russia is Yandex's Chervonenkis (29.41 PFLOPS Rpeak, 1,592 NVIDIA A100 nodes), followed by Yandex's Lyapunov (16.74 PFLOPS), Sber's Christofari Neo (14.90 PFLOPS), and MTS's MTS GROM (2.26 PFLOPS).

Q: What is the median salary of an AI / ML engineer in Russia?

Lead LLM pre-training scientists in Moscow earn a median salary of ₽650,000/month (~$86,000 USD/year), while Senior RLHF engineers earn ₽450,000/month (~$60,000 USD/year), and Middle+ ML engineers earn ₽280,000/month (~$37,000 USD/year).

Q: What is the AKI Sovereign AI Readiness Score for Russia?

AKI benchmarks Russia's sovereign AI readiness at 88.4 / 100 (Tier 1 Sovereign Resilience), reflecting high algorithmic and search independence, native foundation models, and an active compute capacity of over 63.3 PFLOPS.

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🧮 Russian Sovereign AI Resilience & Autonomy Simulator

Evaluates full-stack AI independence across compute scale, domestic dataset purity, and sanctions containment resilience.

        Baseline Active Compute: 63.3 PFLOPS Rpeak

        Hardware Autonomy Rating: 65% Import-Independent

        Domestic Dataset Coverage: 95% Russian Corpus

        Composite Sovereignty Score: 88.4 / 100 (Tier 1 Resilience)