Citi has lowered its price target for NVIDIA to $200 per share from $210, citing growing pressure from Broadcom and Google's tensor processing units. Citi estimates a 4% lower 2026 GPU sales for NVIDIA due to increasing competition from Broadcom and TPUs. The firm believes that AI chipmaker's "moat" is being threatened by other AI chipmakers, leading to the price target cut.
Citi analysts have revised their price target for NVIDIA (NVDA) stock down to $200 per share from $210, citing intensifying competition from Broadcom (AVGO) and Google's tensor processing units (TPUs). The firm has projected a 4% reduction in NVIDIA's 2026 GPU sales due to the increasing pressure from these competitors. This move underscores a shift in the AI chip market landscape, where traditional players like NVIDIA are facing new challenges from specialized AI chipmakers and hyperscalers.
Broadcom's recent quarterly results, which showed strong demand for its AI offerings, have highlighted its growing influence in the AI chip market. The company's strategic pivot toward custom silicon and networking solutions has positioned it as a formidable competitor to NVIDIA. Broadcom's custom AI accelerators, or XPUs, have demonstrated significant performance improvements over general-purpose GPUs, particularly in inference workloads. This capability aligns with the growing demand for energy-efficient, workload-specific solutions in the AI computing market
Why Analysts Call Broadcom a 'Magnificent Eight' Stock That Can Challenge Nvidia[1].
Moreover, Broadcom's networking solutions, such as the Jericho4 router, have enabled distributed AI computing across multiple data centers, addressing latency and scalability challenges. This strength in networking infrastructure further amplifies Broadcom's competitive edge, as it offers end-to-end solutions that NVIDIA lacks
Broadcom’s Strategic Position in the AI Infrastructure Race as a Challenger to Nvidia[2].
Google's entry into the AI chip market with its TPUs also poses a significant threat to NVIDIA's dominance. Google's TPUs are designed to optimize specific workloads, offering performance gains over traditional GPUs. This trend is further supported by hyperscalers' increasing preference for tailored hardware solutions to optimize cost, power efficiency, and control over workloads .
NVIDIA, despite its strong position in AI training, faces fragmentation risks as hyperscalers adopt custom TPUs and diversify their supply chains. The company's market share in AI accelerators is under pressure, and its software ecosystem may face challenges as open-source frameworks and cross-platform compatibility erode its competitive advantage .
Investors should closely monitor these developments as the AI chip market continues to evolve. The increasing demand for energy-efficient, workload-specific solutions suggests that specialized AI chipmakers like Broadcom and Google's TPUs will play a more significant role in the future. NVIDIA's ability to sustain its market share and maintain its software ecosystem will be crucial in this competitive landscape.
References:
Why Analysts Call Broadcom a 'Magnificent Eight' Stock That Can Challenge Nvidia[1] Investopedia. (2025, September 10). Why Analysts Call Broadcom a Magnificent Eight Stock That Can Challenge Nvidia. Retrieved from https://www.investopedia.com/why-analysts-call-broadcom-a-magnificent-eight-stock-that-can-challenge-nvidia-11805620
Broadcom’s Strategic Position in the AI Infrastructure Race as a Challenger to Nvidia[2] AInvest. (2025, September 10). Broadcom Challenges Nvidia's AI Dominance with Custom Silicon and Networking Solutions. Retrieved from https://www.ainvest.com/news/broadcom-strategic-position-ai-infrastructure-race-challenger-nvidia-2509/
AInvest. (2025, September 10). Broadcom AVGO Soars on $10B OpenAI Chip Order. Retrieved from https://nai500.com/blog/2025/09/broadcom-avgo-soars-on-10b-openai-chip-order-nvda-slips/
Comments
No comments yet