IBM, Together AI Launch $240M NVIDIA-Powered Inference Cluster on IBM Cloud

NVIDIA HGX B300

• First large-scale inference cluster with Together AI on IBM Cloud using NVIDIA HGX B300 systems to help enterprises run AI workloads, designed for fast and efficient production

IBM (NYSE: IBM) announced a collaboration with Together AI to deliver IBM and NVIDIA AI infrastructure. Under a multi-year $240M agreement between IBM and Together AI, IBM is positioned to deploy a large cluster of NVIDIA HGX B300 systems on IBM Cloud with expected availability in Q1 2027. Together AI will use this cluster to provide open-source model inference. This deployment is the first dedicated, large-scale cluster built for inference on IBM Cloud using HGX B300 systems and NVIDIA Spectrum-XTM Ethernet networking. According to NVIDIA, it is built to deliver 30x more AI factory output compared to prior generations.

This collaboration aims to enable Together AI to deliver better performance and token economics to enterprises as they look to efficiently scale their AI deployments. Together AI is built on the principle that open-source models are essential for the future of AI and developers should be able to build using open, modular stacks. The company recently raised an $800M Series C financing round at an $8.3B valuation to expand its AI Native Cloud and its platform spans capabilities across inference, training, fine tuning, and agentic workflows. The company reports that it has seen significant momentum for its inference product, now serving 400 trillion tokens monthly.

Together AI selected IBM with NVIDIA because of their innovative product roadmaps and their ability to deliver GPU capacity at the pace required for rapid AI scaling and lowest token cost. Building on IBM's expertise in delivering enterprise-grade cloud capabilities, this collaboration aims to help Together AI to continue its expansion into the enterprise space while making open-source AI more accessible to developers and enterprises around the world.

"Enterprises want the performance of the best frontier models without the closed-model price tag, and that only works if the infrastructure underneath is fast and reliable at scale," said Vipul Ved Prakash, CEO at Together AI. "Working alongside IBM with NVIDIA gives us that foundation. This cluster lets us bring production-grade inference to more companies, faster, and it's a big step in our push to make open-source AI the obvious choice for enterprises."

IBM and NVIDIA Expand Collaboration to Power the Next Wave of AI Innovation

"Enterprises are in a race to adopt agentic AI at scale to drive real business outcomes," said Alan Peacock, General Manager of IBM Cloud. "IBM and NVIDIA are delivering scalable, economical, enterprise-grade AI infrastructure that can help Together AI accelerate innovation for the next generation of AI infrastructure." 

"AI factories are becoming essential enterprise infrastructure—like electricity and telecommunications—turning compute and data into intelligence," said Dion Harris, Senior Director, HPC and AI Infrastructure Solutions, NVIDIA. "With NVIDIA HGX B300 systems and NVIDIA Spectrum-X Ethernet networking on IBM Cloud, IBM and Together AI will deliver an accelerated computing platform to help enterprises deploy open-source AI with the performance, efficiency and scale required for real-time AI services."

This work is the latest example of a larger collaboration between IBM and NVIDIA, who continue to work together to advance AI across infrastructure and software, to deliver performance and efficiency for enterprise and startup clients. A hybrid environment on IBM Cloud powered by NVIDIA GPUs connected with NVIDIA Spectrum-X Ethernet networking and Together AI's inference platform gives organizations a reliable foundation to build, deploy and scale AI systems. Additionally, IBM and NVIDIA recently announced progress across GPU-native data analytics, unstructured data extraction, on-premises and cloud infrastructure, and consulting services. These advancements are designed to help organizations operationalize AI at scale. For more information about the IBM and NVIDIA collaboration, visit www.ibm.com/products/gpu-ai-accelerator/nvidia.

Statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

About IBM

IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain a competitive edge in their industries. Thousands of governments and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM's long-standing commitment to trust, transparency, responsibility, inclusivity and service. Visit www.ibm.com for more information.

About Together AI

Together AI is the AI Native Cloud, combining state-of-the-art open-source models, high-performance infrastructure, and frontier research in AI efficiency and scalability. Founded in 2022, Together AI powers over a million of developers and some of the world's most demanding AI workloads, delivering production-scale inference, training, and reinforcement learning for the next generation of AI-native companies.

Sandisk and SK hynix Drive AI Infrastructure Standardization with High Bandwidth Flash Specification

Sandisk Corporation (Nasdaq: SNDK) and SK hynix Inc. today announced the release of the HBFTM (High Bandwidth Flash) technical specification through the Open Compute Project (OCP), advancing the workstream to drive HBF standardization for the AI inference era, just six months after the consortium began work in February.

The specification was developed through the HBF technology workstream under OCP, with Sandisk and SK hynix serving as primary contributors. Notably, Google and Tenstorrent joined as consortium members during this standardization process, contributing significantly to technology validation and the establishment of the standard. The specification provides companies and developers designing AI inference systems and accelerators with a common technical framework for incorporating HBF technology where larger, near-compute memory capacity and higher bandwidth are needed to improve power and performance metrics and help reduce total cost of ownership.

Modern AI inference systems need high-bandwidth memory positioned close to compute cores, while the demand for greater near-compute memory capacity continues to grow with the requirements of large language models and emerging AI workloads. HBF technology is designed to address this need by combining high bandwidth with high capacity, helping data center system designers improve interactivity and throughput during model serving.

“AI inference is creating a new set of memory requirements, and HBF technology is designed to meet that moment,” said Alper Ilkbahar, Chief Technology Officer, Sandisk. “This specification helps give system designers a practical path to bring high-capacity, high-bandwidth memory closer to compute, while enabling more flexible architectures. It is an important milestone for the HBF ecosystem and for the next generation of AI systems built to improve token economics at scale.”

The specification defines system interface, electrical and other technical guidelines for designing systems that interact with and use HBF technology, including basic performance expectations, the xPU-HBF host interface, reliability and packaging guidance for an HBF die stack, and a software user guide for read and write operations. As one of the first technical standards of its kind in the memory and storage industry, the specification helps give AI compute system designers added flexibility to build systems where HBF technology can coexist with High Bandwidth Memory, helping support ecosystem readiness. The specification was released within the Open Compute Project framework, meaning the information is openly available to the industry. Sandisk and SK hynix proactively published the specification to position HBF technology as the de facto standard in the rapidly evolving AI storage market. Their strategy involves fostering an early-stage ecosystem, increasing the visibility of HBF technology’s adoption for customers, and accelerating market expansion and technological maturity through open collaboration and membership in the consortium.

Sandisk Keynote: NAND - The Versatile & Scalable Foundation of the AI Era

On Wednesday, August 5, at 11:40 a.m. PT, Sandisk’s keynote at The Future of Memory and Storage Conference (FMS) at the Santa Clara Convention Center, will explore the importance of system-level optimization and NAND in enabling AI inference at scale. The keynote will feature Sandisk’s Jim Elliott, chief revenue officer; Khurram Ismail, chief product officer; and Alper Ilkbahar, chief technology officer.

FMS Panel Discussion: Breaking the Memory Wall with High Bandwidth Flash

On Thursday, August 6 at 9:45 a.m. PT, Sandisk, SK hynix, and Google will present a panel discussion hosted by Thomas Coughlin, President of Coughlin Associates, at The Future of Memory and Storage Conference (FMS) at the Santa Clara Convention Center, Conference Room D. The session will discuss how HBF technology aims to redefine the memory hierarchy by providing near-memory speeds with the density and persistence of high bandwidth flash. The panel will bring together experts from HBF solution providers as well as a Hyperscale-AI Infrastructure provider, to dissect the HBF technology usage and development needed for success, including Architectural Integration, Technical Challenges, Standardization timelines, performance and economics.

About Sandisk

Sandisk (Nasdaq: SNDK) delivers innovative Flash solutions and advanced memory technologies that meet people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward.