Side-by-side comparison of AI visibility scores, market position, and capabilities
Palo Alto semiconductor + infrastructure software (NASDAQ: AVGO) at $51.6B FY2024 revenue; AI revenue $12.2B (+220%) from custom XPUs and networking with VMware $69B 2023 acquisition competing with NVIDIA for AI data center infrastructure.
Broadcom Inc. is a Palo Alto, California-headquartered global semiconductor and infrastructure software company — publicly traded on NASDAQ (NASDAQ: AVGO) at approximately $800 billion market capitalization — reporting $51.6 billion in fiscal year 2024 revenue (ended October 2024, 44% year-over-year growth) with AI-related revenue reaching $12.2 billion (220% growth) from custom AI accelerators (XPUs) and networking chips for hyperscale cloud providers. Following the $69 billion VMware acquisition completed in November 2023 (the largest enterprise technology acquisition ever), Broadcom's revenue is now 58% semiconductor and 42% infrastructure software (VMware by Broadcom, CA Technologies products, and Symantec enterprise security). Under CEO Hock Tan's acquisition-driven strategy since 2006, Broadcom has transformed from a moderate-sized fabless semiconductor company into a diversified technology powerhouse with 37,000+ employees. Roots trace to HP Associates (1961), then Agilent Technologies, then Avago Technologies, which acquired Broadcom Corporation in 2016.
Blaize provides purpose-built AI edge compute hardware (Graph Streaming Processor) and AI Studio software; raised $330M+ from DENSO, Mercedes-Benz, Magna, and Samsung; now public on NASDAQ (BZAI).
Blaize is an AI edge computing company that designs purpose-built hardware and software to deploy artificial intelligence applications at the edge — closer to where data is generated rather than in centralized cloud data centers. Founded in 2010 and headquartered in El Dorado Hills, California, Blaize developed the Graph Streaming Processor (GSP), a novel chip architecture optimized for graph-based AI workloads, and AI Studio, a software platform that dramatically simplifies edge AI deployment by reducing the engineering effort required to integrate and run AI models in real-world environments.
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