I’m often asked why international AI models, like those from OpenAI, consistently outperform Russian counterparts such as GigaChat. To understand the gap, we need to look beyond the code and analyze the foundational, structural challenges. Here are the key factors limiting Russia’s position in the global AI race.
1. The Compute Bottleneck
Effective AI development at scale depends on raw computational power. Since 2022, access to essential high-performance NVIDIA chips (like the A100 and H100) has been severed. Training a model on the scale of GPT-4 requires a cluster of over 10,000 GPUs—a resource capacity that simply doesn’t exist in Russia. For context, Sber’s most powerful supercomputer, Christofari Neo, operates at around 12 petaflops, making it 50 to 100 times less powerful than the world’s leading AI research centers.
2. A Widening Investment Gap
Capital is the fuel for innovation. In 2024, Russian AI companies attracted a total of about $34 million in venture funding. Compare that to OpenAI, which has secured over $10 billion, or China’s AI sector, where annual investments reach $20–$30 billion. This financial disparity, measured in orders of magnitude, makes it practically impossible to fund the long-term, capital-intensive research required to build competitive foundational models.
3. Talent Drain and Expertise Shortage
Since 2022, Russia has experienced an exodus of tens of thousands of IT specialists. The incentives are clear: an ML engineer in Russia earns an average of $30,000–$60,000 per year, while the same role in the United States commands $150,000–$200,000. It’s not just about salary; the most ambitious and complex projects are often based abroad, pulling top talent away from the domestic market.
4. Disconnection from the Global Tech Ecosystem
Sanctions have cut off access to critical development and cloud infrastructure tools, including GitHub Copilot, Azure, and Google Cloud. Participation in international conferences and collaborative research has also diminished. While Russia still ranks 14th in AI research publications, its practical integration into the global tech community is shrinking, slowing the flow of new ideas and best practices.
5. A Limited and Insular Market
Ultimately, market dynamics shape technological ambition. The entire Russian AI market was valued at roughly $11 billion in 2023—less than 1% of the global total. More importantly, the rate of AI adoption by businesses in Russia is three times lower than the world average. A primary focus on this small, closed market naturally limits the scale and scope of projects, creating a ceiling for growth and global expansion.