Upscale AI Challenges Nvidia’s Scale-Up Dominance with SkyHammer Fabric and $2 Billion Valuation

For decades, the world’s leading CPU manufacturers have maintained a fiercely proprietary grip on the interconnects used to link multiple processors into shared memory clusters. Whether it was the SMP (Symmetric Multiprocessing) or NUMA (Non-Uniform Memory Access) designs of the past, each vendor developed its own unique "glue" to make a collection of chips behave like a single, massive compute engine. Despite the best efforts of industry consortia like CCIX and CXL to create a universal standard for memory sharing, these attempts largely faltered. Customers may have craved interoperability, but the reality was that few workloads required mixing different CPU architectures, and vendors preferred to innovate on their own schedules without waiting for a standards body to approve new features.

Today, that same battle for proprietary control has shifted from the CPU to the GPU and the XPU. As artificial intelligence workloads demand ever-larger clusters of accelerators, the industry is witnessing the birth of what is now commonly referred to as scale-up networking. At the center of this movement is Nvidia, which has leveraged its proprietary NVLink and NVSwitch technologies to create a dominant position in the AI infrastructure market. However, a well-funded challenger, Upscale AI, is emerging with a vision of a more open, Ethernet-based future for AI fabrics.

The stakes are immense. Nvidia currently charges a significant premium for its NVSwitch and NVLink ports, which provide the high bandwidth and low latency required to connect up to 72 GPUs in a single shared memory domain—a configuration Nvidia calls the NVL72 rackscale machine. While Nvidia has recently begun a "NVLink Fusion" effort, allowing custom CPU and accelerator makers to license NVLink ports to hook into Nvidia’s memory space, it remains a tightly controlled ecosystem. Nvidia has yet to allow customers to build their own independent shared memory systems using their own CPUs and XPUs while merely licensing the NVLink protocol.

This environment of proprietary lock-in is precisely why Upscale AI has captured the attention of the industry and venture capitalists alike. Since its initial $200 million Series A funding round in January, the company’s momentum has accelerated rapidly. Upscale AI has now raised a total of $500 million, seeing its valuation double to $2 billion in less than a year. Its workforce has similarly expanded to over 300 employees, many of whom are veterans of the high-performance networking and systems world. This week, the company’s leadership provided a closer look at "SkyHammer," the scale-up switch ASIC that sits at the heart of its strategy to disrupt the AI networking status quo.

The SkyHammer ASIC is designed to provide an alternative to the proprietary silos currently dominating the market. According to disclosures from Upscale AI’s executive chairman Rajiv Khemani and CEO Barun Kar, the SkyHammer chip boasts an aggregate bandwidth of 115.2 Tb/sec. This figure places the ASIC on equal footing with the highest-end scale-out networking silicon from industry giants like Broadcom, Cisco, and Nvidia. Furthermore, the company’s SkyFabriX architecture is designed to eventually support switch gear with aggregate bandwidth measured in the multiple petabits per second.

Such massive bandwidth is typically achieved by ganging multiple ASICs together within a single switch. This "baby two-tier" approach, often utilized by companies like Broadcom and Meta, allows for a doubling of port bandwidth by using a cluster of independent ASICs where some chips act as downlinks and others act as internal couplers. While this can increase latency due to additional port hops, it is an economically efficient way to scale. Upscale AI appears to be following a similar trajectory, though it has not yet provided a detailed roadmap for future iterations of the SkyHammer silicon.