As AI moves from the lab to the boardroom, Nebius is betting big on the open-source future. The company today launched Nebius Token Factory, a full-stack production inference platform that lets enterprises and vertical AI startups deploy, optimize, and govern open-source or custom models with the kind of scale and reliability usually reserved for hyperscalers.
It’s a bold swing at the next frontier of AI infrastructure: turning open models into production-grade engines capable of handling billions of tokens daily—without sacrificing performance or compliance.
“Every team has unique requirements, and they want speed, reliability and cost efficiency without heavy lifting,” said Roman Chernin, co-founder and Chief Business Officer at Nebius. “We built Nebius Token Factory not just to serve models, but to help customers solve real challenges and engineer for scale.”
The “Waze Moment” for Open AI Infrastructure
Nebius Token Factory arrives at a critical inflection point. As the AI market tilts away from closed proprietary systems like OpenAI’s GPT-4 or Anthropic’s Claude, open alternatives such as Llama 3, Qwen, DeepSeek, and Nemotron are emerging as credible contenders—faster to fine-tune, cheaper to run, and more flexible to deploy.
Yet operationalizing those models remains notoriously painful. Managing GPU clusters, fine-tuning large weights, scaling inference, and maintaining compliance typically require teams with hyperscaler-level expertise. Nebius wants to remove that friction.
Built on Nebius AI Cloud 3.0 “Aether”, the platform promises sub-second latency, 99.9% uptime, autoscaling throughput, and full governance baked in. It supports 40+ open-source models and allows enterprises to host their own custom architectures via OpenAI-compatible APIs, making migration from closed endpoints seamless.
Beyond Performance: Governance and Transparency Built In
Where most inference providers compete on speed, Nebius is betting on trust and control as key differentiators. The Token Factory introduces enterprise-grade governance features like Teams and Access Management, Single Sign-On (SSO), and audit-ready workspaces. It’s designed for organizations juggling complex data residency and compliance mandates across markets.
Security certifications include SOC 2 Type II, HIPAA, ISO 27001, and ISO 27799—a lineup typically associated with high-stakes enterprise IT rather than fast-moving AI startups. Customers can even select zero-retention inference in EU or US datacenters to ensure data never leaves their jurisdiction.
That mix of open flexibility and compliance rigor positions Nebius as something of a “neocloud”—a term industry analysts are using for next-gen cloud providers optimized for AI-specific workloads.
Customers Are Already Seeing Serious Gains
Early adopters are using Nebius Token Factory to power everything from intelligent chatbots to high-performance Retrieval-Augmented Generation (RAG) systems and enterprise copilots.
Prosus, the global tech investor behind brands like OLX and PayU, reports up to 26x cost reductions versus proprietary models. “By leveraging Nebius Token Factory’s dedicated endpoints, Prosus secured guaranteed performance and isolation,” said Zülküf Genç, Director of AI at Prosus. “Autoscaling was the game-changer—handling workloads of up to 200 billion tokens per day without manual intervention.”
Higgsfield AI, a leading video generation startup, turned to Nebius for on-demand and autoscaling inference. “Nebius was the only provider that met our efficiency requirements—reducing overhead, simplifying management, and delivering faster, more cost-efficient AI in production,” said Alex Mashrabov, CEO at Higgsfield AI.
Even Hugging Face, the open-source AI hub, is integrating Nebius infrastructure to deliver faster inference to developers. “Hugging Face and Nebius share the same mission of making open AI accessible and scalable,” said Julien Chaumond, CTO of Hugging Face.
Fine-Tuning Meets Financial Efficiency
Beyond inference, the Token Factory provides an integrated post-training pipeline. Teams can fine-tune or distill large models on their own datasets—using LoRA or full-parameter training—to achieve up to 70% reductions in latency and inference cost. Optimized models can then be deployed instantly to production endpoints, eliminating the need for manual infrastructure setup.
That level of automation turns Nebius into more than a hosting service—it’s a full production lifecycle platform for open models, bridging the gap between experimentation and enterprise deployment.
“AI projects often scale faster than the teams around them,” said Dylan Patel, Chief Analyst at SemiAnalysis. “Nebius’s custom infrastructure gives it one of the lowest total costs of ownership in the GPU cloud market. Token Factory is engineered around the tradeoff triangle: cost, output speed, and model quality.”
A Pragmatic Play for the Open AI Era
In a landscape increasingly polarized between closed giants (OpenAI, Anthropic) and decentralized communities (Mistral, Hugging Face), Nebius is carving out a pragmatic middle path: open, fast, and enterprise-grade.
For AI-native startups and large digital enterprises alike, the promise is compelling—the economics of open models without the operational chaos.
With Token Factory, Nebius isn’t just hosting inference—it’s industrializing open AI, setting the stage for what could become the default way modern companies deploy large models at scale.
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