Supermicro Launches KV Cache Solution with IBM and NVIDIA Demonstrating Significant Inference Performance Benefits
Supermicro Launches KV Cache Solution with IBM and NVIDIA Demonstrating Significant Inference Performance Benefits |
| [05-November-2026] |
SAN JOSE, Calif., Nov. 5, 2026 /PRNewswire/ -- Supermicro, Inc. (NASDAQ: SMCI), an AI, Enterprise, Storage, and 5G/Edge Total IT Solution Provider featuring Data Center Building Block Solutions® (DCBBS), today announced a new KV cache storage solution with IBM and NVIDIA. The joint solution integrates Supermicro Petascale all-flash storage servers using AMD EPYC 9005 Series processors ("Turin"), IBM Storage Scale software, along with NVIDIA Dynamo inference framework software and Spectrum-X Ethernet networking.
Together, these technologies can dramatically reduce the time it takes AI models to begin generating a response, a critical advantage as enterprises adopt agentic and long-context AI workflows. Extending KV cache capacity beyond local GPU memory can improve GPU utilization and inference throughput, while enabling high availability of KV cache content and non-disruptive scaling of KV cache capacity. The result is a more scalable, resilient inference architecture that delivers faster, more responsive AI experiences. "As AI workloads expand from training to inference, enterprises and neoclouds deploying high-throughput inference workloads characteristic of agentic AI and long-context, multi-turn generative AI need to remove bottlenecks to improve GPU efficiency," said Charles Liang, president and CEO of Supermicro. "Our solution with IBM and NVIDIA clearly demonstrates these performance benefits." For a video recap of this release, click here. Inference workloads consist of two phases: prefill and decode. During prefill, input text is converted into tokens and processed by the LLM to generate the intermediate key-value (KV) states needed for inference. By storing these previously computed KV states in a persistent KV cache, the system can reuse them instead of recomputing the same context for subsequent requests. Agentic workflows, coding assistants, long-context RAG, multimodal AI, and multi-turn applications can generate substantial KV state as they process large codebases, documents, conversations, images, and other context, quickly exceeding GPU and CPU memory and driving the need to offload KV cache to high-capacity, shared network storage. The KV cache solution from Supermicro, IBM, and NVIDIA provides this persistent storage layer, helping improve inference efficiency, throughput, and scalability while reducing redundant computation. Key customer benefits of the KV cache solution include:
"Enterprises need a fundamentally better way to scale AI inference. Together, IBM, Supermicro, and NVIDIA are delivering a high-performance, resilient KV cache solution that helps customers maximize their GPU investments, scale independently of compute, and significantly improve infrastructure efficiency," said Sam Werner, GM, IBM Storage. "This collaboration represents an important step toward making enterprise AI inference more scalable, reliable, and cost-effective." "Agentic AI and long-context applications depend on reusing context efficiently across many steps, and NVIDIA Dynamo helps orchestrate distributed inference so enterprises can get more usable throughput from every GPU," said Shruti Koparkar, NVIDIA AI Inference Product Lead. "By pairing NVIDIA Dynamo and Spectrum-X Ethernet with Supermicro Petascale storage servers and IBM Storage Scale, this KV cache solution creates a high-performance shared storage tier that can reduce redundant computation, improve time-to-first-token and help customers scale resilient AI inference services." For more information on Supermicro and IBM solutions click here, and to read the IBM Redbook, Context without Limits: A High-Performance KV Cache Platform for Large-Scale AI Inference, click here. About Super Micro Computer, Inc. Supermicro, Server Building Block Solutions, and We Keep IT Green are trademarks and/or registered trademarks of Super Micro Computer, Inc. All other brands, names, and trademarks are the property of their respective owners. 1Results detailed in IBM Redbook: https://www.redbooks.ibm.com/docs/MD260021/MD260021.html
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Company Codes: NASDAQ-NMS:SMCI,NASDAQ:SMCI |














