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# Broadcom Fires Back at Nvidia with Blazing-Fast Tomahawk Ultra AI Chip
- URL: https://www.theleftshift.com/broadcom-fires-back-at-nvidia-with-blazing-fast-tomahawk-ultra-ai-chip/
- Published: 2025-07-16T08:25:19.000Z
- Updated: 2025-07-16T08:25:19.000Z
- Description: Built on a 5nm process by TSMC, the chip is already shipping, well-positioned to rival Nvidia’s NVLink Switch.
- Author: The Left Shift Bureau
- Tags: Chips

Broadcom has unveiled its latest networking processor, the [**Tomahawk Ultra**](https://investors.broadcom.com/news-releases/news-release-details/broadcom-ships-tomahawk-ultra-reimagining-ethernet-switch-hpc?ref=theleftshift.com), aiming to redefine AI infrastructure by enabling ultra‑fast connectivity between hundreds of GPUs inside data centres. 

Built on a **5nm process by TSMC**, the chip is already shipping, well-positioned to rival **Nvidia’s NVLink Switch** in the fierce AI hardware competition.

Tomahawk Ultra switch redefines Ethernet for AI and HPC with 250ns ultra-low latency, 51.2 Tbps throughput, and 77B packets/sec capacity. It features optimised Ethernet headers, cutting overhead to 10 bytes, and ensures lossless data transfer with Link Layer Retry and Credit-Based Flow Control for peak reliability and performance.

“Tomahawk Ultra is a testament to innovation, involving a multi-year effort by hundreds of engineers who reimagined every aspect of the Ethernet switch. This highlights Broadcom’s commitment to invest in advancing Ethernet for high-performance networking and AI scale-up,” [Ram Velaga](https://www.linkedin.com/in/ram-v-124b79/?ref=theleftshift.com), senior vice president and general manager of Broadcom’s Core Switching Group, said.

Designed originally for **high-performance computing**, the platform has been adapted to serve **generative AI workloads**, where efficient “scale-up” computing—connecting GPUs in close proximity—is critical. 

"Tomahawk Ultra is 100% pin-compatible with Tomahawk 5, ensuring a very fast time-to-market. It is shipping now for deployment in rack-scale AI training clusters and supercomputing environments," the company said in a press release.