Intel Corporation has announced a collaboration with RadixArk to advance open AI inference on Intel platforms. Under the partnership, both companies will optimize SGLang, an open-source AI inference stack, for Intel hardware. The effort aims to help developers and enterprises deploy leading AI models more efficiently. Likewise, it will help them build AI applications at a lower cost.
Anil Nanduri, vice president, AI Products & GTM, Intel Data Center Group, outlined the thinking behind the move.
“Enterprise AI is moving beyond isolated performance benchmarks to solving full-system production deployments,” said Anil Nanduri, vice president, AI Products & GTM, Intel Data Center Group. “This collaboration ensures developers have Day-0 readiness and high-performance inference software directly optimized for Intel CPUs, GPUs and accelerators with an open approach and gives them the freedom to choose the tools, frameworks and technologies that best fit their needs.”
Why Open AI Inference Matters for Enterprises
AI models continue to grow larger and more complex. As a result, enterprises now need heterogeneous, open inference infrastructure. Moreover, delivering AI in production demands that every prompt reaches the right place. Each workload must also match the right intelligence, the right compute, and the right economics.
This is where open inference runtimes step in. They provide the essential connective tissue for full-stack deployments. Therefore, these deployments become practical, reliable, and economically sustainable across diverse enterprise environments.
What the Collaboration Delivers for Developers
The collaboration expands developer choice for deploying leading AI models on enterprise-proven Intel hardware. Model builders and software engineers can build and innovate on standard, open frameworks and interfaces. At the same time, they can take full advantage of Intel’s compute density. They also gain access to built-in hardware acceleration features, including Intel Advanced Matrix Extensions (Intel AMX).
Open AI inference, developers gain faster time-to-production and reduced latency. They also get flexible deployment options across existing data centers and cloud capacity.
RadixArk shared its perspective on the milestone as well.
“Our collaboration with Intel is a major milestone for open-source AI inference, enabling SGLang optimization directly to Intel’s platforms,” said Ying Sheng, CEO, RadixArk. “By upstreaming deep optimizations into the core framework, we are eliminating constraints and ensuring developers never have to compromise between open standards and high performance. Our mission to make frontier AI infrastructure open and accessible to every builder, and Intel’s enterprise-ready architecture gives development teams the flexibility and compute density they need to scale production AI workloads seamlessly.”
An Open Blueprint for Production AI
Notably, the collaboration brings hardware and software optimization together. This reflects Intel’s approach of contributing improvements directly to community software. Intel does not treat these improvements as separate deployment decisions.
Furthermore, these upstream contributions go to popular engines and frameworks. They aim to provide high-performance paths for turning breakthrough models into scalable, production-grade applications. Meanwhile, the approach preserves flexibility, choice, and broad architectural freedom for developers and enterprises alike.
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News Source: Businesswire.com
