Nebius

Your team is arguing fine-tuning versus RAG. A vendor just quoted you a per-token price. Someone says the agent needs tool access before it's useful. Technical decisions should follow business needs, not lead them. The Nebius AI Leader Certification covers the fundamentals behind those decisions: AI basics and building AI products with models accessed through providers like Nebius Token Factory. Passing means you're able to evaluate AI options and explain the trade-off with confidence and expertise. Nebius Academy graduate Aleksandr Dzhumurat put it this way: “I can now walk colleagues through the real choices in plain terms: fine-tuning vs. RAG, why an LLM needs tools to fetch live data, when structured output beats a free-form answer.” 60 minutes, 20–30 multiple-choice questions, online whenever suits you, no prerequisites. Pass and you get a verifiable certificate, a Credly badge, and free credits to build with. $1 during early bird, $100 after. https://lnkd.in/g8E_9a5Q

Nebius was built on the conviction that AI should stay competitive and diverse, rather than consolidate around a handful of models controlled by a handful of companies. In his first post since joining as SVP Research, Matthew Zeiler makes the case that the future of AI won't be decided by whether open weights exist, but by whether the system around them makes them competitive in production. The post is also a record of what that looks like in practice: Soperator, our server designs at OCP, SWE-Rebench, the Agents Blueprint, day-zero support for new open models, and our own console agent Echo running on open models. The whole AI stack moves faster in the open. https://lnkd.in/d3dv2i-r

Everyone at Nebius seems to tell a similar story about their first weeks, Mashrur Haider 🕶️ included. “You join and start contributing from day one. Your first assignment is usually something complex and genuinely impactful. You are trusted to take ownership, learn fast, and rise to the challenge. Once you do, the next opportunity follows.” That kind of leap wasn’t new for him. Before Nebius, he founded a biotech startup, where he developed the instincts he’d bring to the current role: learning quickly, reasoning from first principles, and taking calculated chances where required.  "Making decisions with suboptimal information," as he puts it. The Nebius culture matched that startup pace. With ambitious targets in an engineer-led team, people discuss challenges openly, tackle work head-on, and participate proactively to reach solutions faster. For Mashrur, that means leading products across the model lifecycle, from post-training to dedicated inference. "If you want to work on state-of-the-art technology, competing alongside the top 0.01% in the world, this is one of the few places to go." Find your role with us: https://lnkd.in/e_U8Q43N #BuildersatNebius 

Benchmarking speed alone isn't enough. Production inference needs to be fast *and* accurate. We're excited to see Artificial Analysis launch the Endpoint Accuracy Index, helping bring more transparency to how well inference providers preserve model quality. It's great to see the conversation expanding beyond latency to include correctness as a first-class metric.

Lindsey Irvine has joined Nebius as Chief Marketing Officer. She has scaled marketing globally at Square, helped build new markets at Benchling, and driven significant growth at MuleSoft. We're glad to have you with us, Lindsey!

Most teams can build an AI agent. But building one that’s reliable, observable, and cost-effective in production remains a real challenge. On Tuesday, August 4th, we're closing that gap live in a webinar, and you’re invited. Join Nebius, LangChain, and Tavily as we build a compliance audit agent from a real-world case study, first deployed using the Nebius Agents Blueprint, then rebuilt with LangChain Deep Agents on NVIDIA Nemotron 3 Ultra. The result is frontier-level quality at roughly one-tenth of the cost, with no model fine-tuning required. You’ll leave with: - A measured comparison of open-model and frontier-model agent architectures showing the real quality and cost trade-offs, on the same task - Grounding and retrieval with Tavily and Pinecone, observability with LangSmith, simulation testing with Snowglobe - The complete architecture and code, so you can reproduce the implementation after the session Leading the build: Devang Sachdev and Tikhon Roshchupkin (Nebius), Srimanth Tangedipalli (LangChain), and Lakshya Prakash Agarwal (Tavily, part of Nebius Group). Can't join live? Register anyway! Everyone who signs up gets the recording. https://lnkd.in/edktgARW

What does building sustainably look like from the inside?   Today, we published our second annual Sustainability Report, covering how we build our AI cloud to deliver more high-performance compute while using fewer resources.   Our Head of Sustainability, Daria Mukhortova, sat down with the leaders involved to discuss what it takes to make this possible: the hardware choices, the community conversations, and why we build for efficiency from day one.   Hear the conversation: https://lnkd.in/dcZuJb6n

Higgsfield created a 95-minute feature film in 14 days, with a $500,000 budget and a team of 15. It was built on Nebius. And while Hell Grind premiered in about as classic a context as you could imagine, at the Cannes Marché du Film, the production context was anything but traditional. Higgsfield's Soul Cinema and Cinema Studio gave the team cinematic control over AI-generated video: 300–500 variations per scene, video prompts running 3,000–4,000 words, and character consistency held across the full 95 minutes. It cost about 100× less than traditional movie workflows require at this length. What made it viable is inference economics. Hell Grind's overnight batch generation meant spinning up hundreds of NVIDIA Blackwell GPUs, then scaling them back down by morning. Nebius delivered a custom configuration that improved Higgsfield's inference performance by over 20%. Today, Higgsfield runs around 30 billion tokens per day through Nebius AI Cloud. When inference economics hits the right inflection point, a 15-person team can ship a feature film in two weeks. Higgsfield plans to open-source Hell Grind so other creators can see exactly how it was done. Watch the behind-the-scenes story: https://lnkd.in/eSEP73Vv

The Physical AI Summit is back. Applications for the 2026 Nebius Physical AI Awards are now open. On November 3, the Nebius Physical AI Summit returns to San Francisco, bringing together founders, developers, researchers, investors, and industry leaders shaping the future of intelligent machines. As part of this year's Summit, we're inviting Physical AI startups to apply for one of the industry's premier global competitions recognizing innovation in Physical AI. Each winning startup will receive $150,000 in Nebius AI Cloud compute credits accelerated by NVIDIA AI infrastructure. Finalists will be invited to the Summit, where they will present their work. Winners will be announced live during the Awards Ceremony. Awards will be presented across five categories: • Physical AI Models • Perception & Spatial Intelligence • Simulation & Synthetic Data • Systems & Deployment • Software, Tooling & Orchestration Entries will be evaluated by a distinguished jury including leaders from Nebius, NVIDIA, and other top global technology companies and academic institutions. Applications are open through September 30. Apply today: https://lnkd.in/eyNX6gWt