NVLink Fusion
Last reviewed
May 31, 2026
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v5 · 1,736 words
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Last reviewed
May 31, 2026
Sources
10 citations
Review status
Source-backed
Revision
v5 · 1,736 words
Add missing citations, update stale details, or suggest a clearer explanation.
NVLink Fusion is a program and silicon technology from NVIDIA that opens its NVLink high speed interconnect to third party chips. It lets partners connect their own CPUs and custom accelerators to NVIDIA GPUs, or attach their own accelerators to NVIDIA CPUs, so they can build semi custom rack scale AI systems that still plug into NVIDIA's interconnect fabric. NVIDIA introduced it at Computex in Taipei on May 18, 2025, framing it as a way for the wider industry to build specialized AI infrastructure around NVLink rather than only buying complete NVIDIA systems. [1][2]
The announcement matters because NVLink had been closed. For years it worked only between NVIDIA's own GPUs and, through a related link, between NVIDIA GPUs and NVIDIA's Grace CPUs. NVLink Fusion changes that by selling the interconnect as licensable building blocks. Partners can drop NVLink into their silicon and join racks that NVIDIA also populates. The move arrived as cloud providers design more of their own chips and as a competing open standard, UALink, gathered backing from several of NVIDIA's largest rivals. [3][4]
NVLink is NVIDIA's scale up fabric, the wiring that ties many accelerators together inside a server or a rack so they behave more like one large machine. The fifth generation used in Blackwell systems delivers up to 1.8 terabytes per second of bidirectional bandwidth per GPU, which NVIDIA describes as roughly 14 times the bandwidth of a PCIe Gen5 link. That gap is the reason NVLink exists. Large model training and high throughput inference move enormous amounts of data between chips, and a standard PCIe connection becomes a bottleneck. [2][5]
NVLink Fusion takes that same fabric and packages it so non NVIDIA silicon can join. NVIDIA offers it in two delivery forms. A partner can integrate NVLink interface IP directly into a chip design, or it can place an NVIDIA built NVLink chiplet next to its silicon in the same package. Either way the resulting part can speak NVLink to NVIDIA hardware across the rack. The word semi custom is the key idea. The customer brings custom silicon, and NVIDIA supplies the connective tissue plus at least one class of its own chips in the system. [3][5]
NVLink Fusion supports two configurations, pointed in opposite directions.
The first path connects a partner's custom CPU to NVIDIA GPUs. Here the partner integrates NVLink chip to chip IP, the same family of technology NVIDIA calls NVLink-C2C, into its processor. NVLink-C2C is the short reach link NVIDIA already uses to bind its Grace CPU to its GPUs at high bandwidth. By licensing that interface, a company can build a CPU that sits next to NVIDIA GPUs and feeds them as tightly as NVIDIA's own Grace part would. Fujitsu and Qualcomm are the named CPU partners taking this route, each pairing custom processors with NVIDIA GPUs. [1][6]
The second path runs the other way. A hyperscaler or chip designer builds a custom accelerator, often called an XPU or an ASIC, and places an NVLink chiplet beside it. That chiplet lets the accelerator plug into NVIDIA's NVLink rack fabric, the same switched network used in systems like the GB200 NVL72, so the custom part can scale up alongside or in place of NVIDIA GPUs. Custom silicon firms such as Marvell, MediaTek, and Alchip support this direction. [2][3]
In both cases the racks can keep using NVIDIA's networking for the scale out side, the links between racks and across the data center. That includes Spectrum-X Ethernet and ConnectX network interface cards, which gives partners a path to grow an AI factory to very large GPU counts while reusing NVIDIA's end to end stack. [1][2]
NVIDIA grouped its launch partners by what they contribute. Custom silicon designers build the chips. Two firms supply CPUs that link to NVIDIA GPUs. Electronic design automation vendors, the companies whose tools engineers use to design chips, provide the IP and the flows that make integrating NVLink practical. A connectivity specialist supplies the physical fabric components.
| Partner | Role in NVLink Fusion |
|---|---|
| MediaTek | Custom silicon design for accelerators that scale up over NVLink |
| Marvell | Custom silicon and ASIC design for NVLink connected accelerators |
| Alchip Technologies | Custom ASIC design services for NVLink Fusion silicon |
| Astera Labs | Connectivity components and fabric silicon for NVLink Fusion systems |
| Cadence | EDA tools and IP for integrating NVLink interfaces into chip designs |
| Synopsys | EDA tools and IP for integrating NVLink interfaces into chip designs |
| Fujitsu | Custom CPUs that connect to NVIDIA GPUs over NVLink |
| Qualcomm Technologies | Custom CPUs that connect to NVIDIA GPUs over NVLink |
The mix is deliberate. None of these companies sells a data center GPU that competes head to head with NVIDIA. The CPU partners extend NVIDIA's reach into processors. The design service and EDA firms help customers build accelerators that still need NVIDIA's fabric to scale. So NVIDIA opens the door to custom silicon while keeping its GPUs central to the rack. [1][3][7]
NVLink Fusion is a shift in how NVIDIA sells. The traditional model was to ship complete chips and complete systems. NVLink Fusion adds a licensing model layered on top, where NVIDIA earns from the interconnect and the surrounding platform even when a customer builds part of the silicon itself. [4][7]
The timing tracks the rise of custom accelerators. The largest cloud companies have been designing their own AI chips to cut cost and reduce dependence on any single vendor. Left unaddressed, that trend would route spending away from NVIDIA. NVLink Fusion offers those customers a middle path. They can deploy custom parts and still buy into NVIDIA's rack architecture, its networking, and its software. As Jensen Huang, NVIDIA's founder and chief executive, put it, "NVLink Fusion opens NVIDIA's AI platform and rich ecosystem for partners to build specialized AI infrastructure." [1]
The competitive backdrop is UALink. The Ultra Accelerator Link effort is an open, consortium governed standard for connecting accelerators at scale, backed by AMD, Broadcom, Intel, Google, Microsoft, Meta, and others. Its pitch is an accelerator to accelerator fabric that needs no NVIDIA component. NVLink Fusion is widely read as NVIDIA's answer. Where UALink asks the industry to standardize around a neutral spec, NVIDIA offers its own mature fabric on licensable terms and keeps itself in the loop. [3][4][8]
NVLink Fusion does not replace NVLink. It is the same fabric, repackaged for outside silicon. Inside NVIDIA's own products NVLink keeps doing what it always did, tying GPUs together and, through NVLink-C2C, tying the Grace CPU to NVIDIA GPUs. NVLink Fusion exposes those interfaces so partners can build the same kinds of connections from their side. [2][5]
The reference point is the rack scale systems NVIDIA already ships. A GB200 NVL72 connects 72 Blackwell GPUs into a single NVLink domain through NVLink switches, so the whole rack acts like one accelerator for a large job. NVLink Fusion lets a partner's custom CPU or custom accelerator participate in that style of domain rather than sit outside it on a slower link. The follow on architectures NVIDIA has outlined, including Vera Rubin, continue the same scale up approach, which gives NVLink Fusion a long runway. [2][5]
For NVIDIA the program is a hedge. If custom silicon keeps growing, NVLink Fusion captures some of that spending through interconnect licensing, networking, and rack design instead of losing it outright. For partners it lowers the bar to building competitive rack scale systems, since they can lean on a proven fabric rather than invent one. [4][7]
The main criticism is that it is not truly open. Every NVLink Fusion configuration still requires NVIDIA silicon at its center, a GPU or a CPU, and NVIDIA controls the specification. You cannot, for example, link a non NVIDIA CPU to a non NVIDIA accelerator over NVLink Fusion. If you bring a custom CPU you connect it to NVIDIA GPUs, and if you bring a custom accelerator you connect it to an NVIDIA CPU. Customers can add their own chips, but only inside a system that remains tethered to NVIDIA's platform. Reporters and analysts contrasted this with UALink, which needs no NVIDIA part and is governed by a neutral body. The reading was that NVLink Fusion lets NVIDIA look open while preserving its lock in. [3][4][8]
The partner list reinforced that view. The most direct GPU rivals, AMD, Broadcom, and Intel, were absent, and they sit on the UALink side instead. The companies that signed on were custom silicon designers, EDA vendors, and CPU makers that do not compete with NVIDIA's accelerators. [3][8]
NVLink Fusion is a program with a defined shape rather than a blank check. It assumes NVIDIA hardware in the rack, so it does not enable an all third party system. It is delivered as IP and chiplets that partners must design into silicon, which means real adoption shows up only as those custom parts tape out and ship, a process that takes time after an announcement. The early news named partners and roles, and several technical specifics beyond the headline bandwidth figures and the two configurations were left for later disclosure. [1][3][5]