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Nvidia is expanding its AI dominance by opening up its NVLink ecosystem to rivals. CEO Jensen Huang unveiled NVLink Fusion at Computex 2025, allowing non-Nvidia CPUs and accelerators to integrate with Nvidia's AI infrastructure. This move allows customers to use CPUs, GPUs, and accelerators from other vendors alongside Nvidia GPUs, all tied together using Nvidia’s high-bandwidth NVLink interconnect. Key partners include MediaTek, Marvell, Fujitsu, and Qualcomm, and the program allows customers to use CPUs, GPUs, and accelerators from other vendors alongside NVIDIA GPUs, all tied together using NVIDIA’s high-bandwidth NVLink interconnect.
This strategic positioning ensures Nvidia remains central to AI data centers, even when customers use rival chips. Huang stated that NVLink Fusion enables the building of "semi-custom AI infrastructure, not just semi-custom chips," emphasizing that every such system runs through Nvidia's ecosystem, including its GPUs, interconnects, and software stack. The resulting intellectual property package is called NVLink Fusion, meaning that those making custom CPUs or accelerators can license the NVLink port designs and the memory atomic protocol that rides on top of it to allow a kind of NUMA memory sharing akin to that which has been available for CPUs for several decades now. Nvidia is also partnering with Foxconn to build an AI supercomputer in Taiwan, which will help fuel Taiwan's innovation. The supercomputer will utilize 10,000 Nvidia Blackwell GPUs. Taiwan’s National Science and Technology Council will use this supercomputer to deliver AI cloud computing muscle to Taiwanese organizations, making it easier for the country to adopt AI tech across private and public institutions. TSMC, Nvidia’s main supplier, intends to use it for R&D with the AI supercomputer said to have “orders-of-magnitude faster performance, compared with previous-generation systems”. Recommended read:
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@blogs.nvidia.com
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NVIDIA is significantly expanding its presence in the AI and quantum computing landscape through strategic partnerships and infrastructure developments. The company is opening its NVLink ecosystem to allow non-NVIDIA chips to integrate seamlessly, a move designed to solidify NVIDIA's central role in AI infrastructure, even with the use of competitor's silicon. This initiative, known as NVLink Fusion, allows for semi-custom AI infrastructure, enabling companies to combine processors from vendors like MediaTek, Marvell, Fujitsu, and Qualcomm with NVIDIA GPUs, all interconnected by NVIDIA's high-bandwidth NVLink technology. NVIDIA CEO Jensen Huang envisions an AI infrastructure industry worth trillions of dollars, emphasizing that these AI data centers, or "AI factories," produce valuable "tokens" by applying energy.
These expansions extend beyond traditional AI, with NVIDIA actively collaborating with partners to advance quantum computing. Silicon developers like Compal, Quanta, and Taiwan's National Center for High-Performance Computing are leveraging NVIDIA AI supercomputing hardware to accelerate quantum computing research. Furthermore, NVIDIA is partnering with Foxconn to build a state-of-the-art AI supercomputer in Taiwan. This supercomputer, equipped with 10,000 NVIDIA Blackwell GPUs, aims to provide AI cloud computing resources to Taiwanese organizations and support research and development for TSMC, the world's largest chipmaker. NVIDIA's strategic collaborations also include international partnerships, such as the launch of the ABCI-Q supercomputer in collaboration with Japan’s National Institute of Advanced Industrial Science and Technology (AIST). This system, powered by NVIDIA H100 GPUs and Quantum-2 InfiniBand, supports large-scale hybrid quantum-classical computing. By integrating NVIDIA's CUDA-Q platform, ABCI-Q enables researchers to simulate and accelerate quantum applications, further cementing NVIDIA's role in advancing both AI and quantum computing technologies. These efforts signal a commitment to driving innovation and facilitating the development of groundbreaking solutions across various industries. Recommended read:
References :
@blogs.nvidia.com
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NVIDIA is significantly expanding its presence in the AI ecosystem through strategic partnerships and the introduction of innovative technologies. At Computex 2025, CEO Jensen Huang unveiled NVLink Fusion, a groundbreaking program that opens NVIDIA's high-speed NVLink interconnect technology to non-NVIDIA CPUs and accelerators. This move is poised to solidify NVIDIA's role as a central component in AI infrastructure, even in systems utilizing silicon from other vendors, including MediaTek, Marvell, Fujitsu, and Qualcomm. This initiative represents a major shift from NVIDIA's previously exclusive use of NVLink and is intended to enable the creation of semi-custom AI infrastructures tailored to specific needs.
This strategy ensures that while customers may incorporate rival chips, the underlying AI ecosystem remains firmly rooted in NVIDIA's technologies, including its GPUs, interconnects, and software stack. NVIDIA is also teaming up with Foxconn to construct an AI supercomputer in Taiwan, further demonstrating its commitment to advancing AI capabilities in the region. The collaboration will see Foxconn subsidiary, Big Innovation Company, delivering the infrastructure for 10,000 NVIDIA Blackwell GPUs. This substantial investment aims to empower Taiwanese organizations by providing the necessary AI cloud computing resources to facilitate the adoption of AI technologies across both private and public sectors. In addition to hardware advancements, NVIDIA is also investing in quantum computing research. Taiwan's National Center for High-Performance Computing (NCHC) is deploying a new NVIDIA-powered AI supercomputer designed to support climate science, quantum research, and the development of large language models. Built by ASUS, this supercomputer will feature NVIDIA HGX H200 systems with over 1,700 GPUs, along with other advanced NVIDIA technologies. This initiative aligns with NVIDIA's broader strategy to drive breakthroughs in sovereign AI, quantum computing, and advanced scientific computation, positioning Taiwan as a key hub for AI development and technological autonomy. Recommended read:
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Joe DeLaere@NVIDIA Technical Blog
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NVIDIA has unveiled NVLink Fusion, a technology that expands the capabilities of its high-speed NVLink interconnect to custom CPUs and ASICs. This move allows customers to integrate non-NVIDIA CPUs or accelerators with NVIDIA's GPUs within their rack-scale setups, fostering the creation of heterogeneous computing environments tailored for diverse AI workloads. This technology opens up the possibility of designing semi-custom AI infrastructure with NVIDIA's NVLink ecosystem, allowing hyperscalers to leverage the innovations in NVLink, NVIDIA NVLink-C2C, NVIDIA Grace CPU, NVIDIA GPUs, NVIDIA Co-Packaged Optics networking, rack scale architecture, and NVIDIA Mission Control software.
NVLink Fusion enables users to deliver top performance scaling with semi-custom ASICS or CPUs. As hyperscalers are already deploying full NVIDIA rack solutions, this expansion caters to the increasing demand for specialized AI factories, where diverse accelerators work together at rack-scale with maximal bandwidth and minimal latency to support the largest number of users in the most power-efficient way. The advantage of using NVLink for CPU-to-GPU communications is that it offers 14x higher bandwidth compared to PCIe 5.0 (128 GB/s). The technology will be offered in two configurations. The first will be for connecting custom CPUs to Nvidia GPUs. NVIDIA CEO Jensen Huang emphasized that AI is becoming a fundamental infrastructure, akin to the internet and electricity. He envisions an AI infrastructure industry worth trillions of dollars, powered by AI factories that produce valuable tokens. NVIDIA's approach involves expanding its ecosystem through partnerships and platforms like CUDA-X, which is used across a range of applications. NVLink Fusion is a crucial part of this vision, enabling the construction of semi-custom AI systems and solidifying NVIDIA's role at the center of AI development. Recommended read:
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