Red Hat leverages open source AI tools like Red Hat AI 3, vLLM, llm-d, and KubeVirt to give enterprises flexible, interoperable, and scalable AI infrastructure.
Red Hat has launched Red Hat AI 3, an open source distributed inference engine integrated natively into Kubernetes, providing a unified collaboration layer for developers, operators, and data teams. Key tools such as AI Hub, Gen AI Studio, and Model as a Service enable shared workflows across teams.
Paul Nashawaty, practice lead and principal analyst at theCUBE Research, said, “These combined features transform Red Hat AI 3 into an enterprise collaboration fabric for AI, where developers, operators and data teams share one control plane, one governance model and one source of truth.”
Red Hat has focused on open-source models to drive innovation, with rapid improvements enabling both business and consumer use cases. Robert Shaw, director of engineering at Red Hat, noted, “Reasoning capabilities that have been added to some of the proprietary models are starting to show up in the open-source models. There is continued improvement in the overall quality of those open-source models, which is what actually unlocks the business use cases and consumer use cases that are powering all this frenzy.”
The company emphasises interoperability, allowing enterprises to integrate their own tools while maintaining transparency, reliability, and flexibility. Jennifer Vargas, senior principal marketing manager at Red Hat, said, “One of the things that we do is to make sure that we give customers interoperability … when everyone’s looking for an AI that’s transparent, that is trustworthy, that is reliable.”
Emerging technologies such as vLLM and llm-d offer scalable, memory-efficient open-source AI model serving, while KubeVirt integrates virtual machines with Kubernetes for hybrid workloads. Ashesh Badani, chief product officer at Red Hat, highlighted, “We’re one of the creators of the KubeVirt project … the number of customers that we’ve got probably has tripled … we are seeing a huge amount of interest in this area.”
Red Hat also focuses on security and zero-trust AI, embedding ongoing verification, access controls, and compartmentalisation to protect AI workloads. Rob Strechay, theCUBE Research, added, “Red Hat looks to unveil a strategy to secure AI models throughout the entire lifecycle.”
