Arkady says we are building the company in three dimensions: Scale: more mega- and gigawatts of compute infrastructure, plus capital Product: bare metal → cloud → token factory → agentic Customers: AI natives → ISVs → enterprises And the fourth dimension (like time as the fourth dimension with the three spatial dimensions) is the company and team itself: how we mature, grow, and improve.

Inflection event was built around a very simple purpose: tell what we do to those who care. I’d even say Reflection would have been a better name:) The run is so fast that sometimes you need to take time not to announce something new, but to reflect on WHY and WHAT we are.

Actually, the perfect summary. That’s what we do. Build 4 layers of the AI cloud.

Here we go

NVIDIA Nemotron™ 3 Ultra is now live on Nebius Token Factory. It’s built for long-running agents across coding, deep research and enterprise workflows. Nemotron 3 Ultra delivers frontier reasoning with up to 5x faster inference and up to 30% lower cost for agentic workloads. For builders, the next question is production: performance, reliability, economics and control. Run it today: tokenfactory.nebius.com/mode…

🎓 It's summertime, and Nebius’s Early Talent Program is here. Over the next few months, recent graduates and people taking their first steps in tech will join teams across Nebius locations around the world to work on real projects and learn from experienced engineers and researchers! 1/4

Excited to see @nebiustf and @tavilyai at the slide We've just started building

we badly need strong open-source models, and who is better positioned to deliver them in the "western" world?

Wow! @recraftai, @AnnaVDorogush, and the team are crushing it!

Growth is basically a never-ending game of unlocking the next bottleneck. Every time, the question is the same: what’s the most important thing to fix now? Capacity, demand, delivery, models performance, field, hiring... and so on and so forth

My [optimistic] thinking: Anthropic’s insane revenue growth and the huge number of tokens it generates show what will happen next with open-source / alternative model tokens. Start with frontier models → grow usage → collect data → tune cheaper models -> get margins.

People I need to meet next time in the bay area?

That’s how we do it:)

Today, we're announcing that Eigen AI is joining Nebius (NASDAQ: NBIS). From day one, our mission has been Artificial Efficient Intelligence — building the world's most efficient engines for generating intelligence. Together with Nebius, we're working toward the best AI cloud, uniting Eigen's full-stack model and inference software, ranked #1 on Artificial Analysis for inference speed, with Nebius's global hardware and infrastructure footprint, so any developer or enterprise can run the best models at the best price, with no capacity ceiling. After close, Eigen's optimization stack will be integrated directly into Nebius Token Factory. The entire Eigen AI team is joining Nebius in full, establishing Nebius's engineering and research presence in the San Francisco Bay Area. To our customers, our team, our investors at Tectonic Ventures, E14 Fund, Uncorrelated Ventures, and AGI House Ventures, our angel investors, advisors, mentors, and supporters — and to the Nebius team for the conviction and partnership — thank you. The mission doesn't change. The leverage behind it does. Ryan Hanrui Wang, co-founder and CEO of Eigen AI, said: “We’re proud to join Nebius and work alongside the Token Factory team to push the boundaries of inference performance. Nebius has built a world-class AI cloud with a deep engineering culture that perfectly aligns with our own. Together, we are removing the friction of AI model customization and deployment so developers can run models reliably in production without managing the underlying infrastructure.” Full announcement at: eigenai.com/blog/eigen-ai-jo…

265 tokens/sec on Kimi K2.6. @Eigen_AI_Labs leading the pack ⚡ Eigen 🤝 Nebius Token Factory

Everybody’s talking about data gravity. But the reality is that inference generates tons of new data. At @nebiustf, we’re taking a step toward helping builders collect, curate, and use that data as they build applications at scale. nebius.com/services/token-fa…

Data Lab is the workspace where production logs and existing data become reusable datasets for model improvement. Explore inference data, filter real-world signal, connect files from S3-storage, and move curated datasets into post-training without stitching tools together.