Piper Sandler analyst Harsh V. Kumar reiterated an Overweight rating on $NVIDIA (NVDA.US)$ with a $1,050 price target, his top large-cap pick.
During his recent AI Discovery Bus Tour, Kumar engaged directly with Nvidia's management team, which allowed him to delve deeper into the company's current operations and future prospects.
Despite being in the market for nearly two years, the demand for Nvidia's Hopper GPU remains robust, with the supply needing to catch up, as per the analyst.
He said the supply-demand imbalance will likely continue throughout the year, potentially offering a slight margin boost until the introduction of the Blackwell GPU.
As per Kumar, the launch of the Blackwell GPU later this year will likely mirror the supply and demand challenges faced by Hopper.
Customers are reluctant to switch their orders from Hopper to Blackwell, fearing even longer wait times due to anticipated supply constraints.
Nvidia's management addressed concerns about the power requirements for upcoming data centers, who assured that their accelerated computing solutions are significantly more power-efficient than traditional computing, Kumar said.
Plans are in place to optimize power needs for future data centers, including leveraging "trapped power" in specific regions and considering new data centers in countries that can meet these significant power demands.
Pricing discussions centered on the Total Cost of Ownership (TCO) benefits provided by Nvidia to its customers, indicating no change in pricing philosophy with the introduction of the Blackwell architecture, he said.
While the company aims to maintain competitive pricing, gross margins for the Blackwell architecture will likely be slightly below the corporate average as it ramps up.
Revenue opportunities from data center products sold to sovereign entities are currently being realized by Nvidia, with expectations for this demand to significantly contribute to the company's revenue in the near term, as per Kumar.
The move towards liquid-cooled systems, especially with the GB200, is another area of innovation, with major Cloud Service Providers committing to adopting the GB200, primarily for inference applications.
In terms of valuation, Nvidia's shares are trading at a premium compared to its peers, reflecting Nvidia's continued leadership and innovation in the GPU market.
Kumar projected first-quarter revenue and EPS of $24.01 billion and $5.41.
After hosting an industry expert on the data center and AI supply chain, Mizuho analyst Vijay Rakesh noted Nvidia's leading AI GPU with a strong software moat. He also said Nvidia is leading AI accelerators, especially for training.
Nvidia continues to be the AI leader, with continued tightness on H100 and H200. Blackwell B100 is set to launch in 2024 and ramp up in 2025, as per the analyst.
However, he also flagged some potential challenges with new high-power Nvidia systems with power-to-rack and cooling solutions, a major data center challenge.
Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors.
派珀·桑德勒分析師哈什·庫馬爾重申了增持評級 $英偉達 (NVDA.US)$ 目標股價爲1,050美元,這是他的首選大盤股。
在最近的人工智能探索巴士之旅中,庫馬爾直接與英偉達的管理團隊進行了接觸,這使他能夠更深入地研究公司當前的運營和未來前景。
分析師稱,儘管上市了將近兩年,但對Nvidia的Hopper GPU的需求仍然強勁,供應需要迎頭趕上。
他說,供需失衡可能會持續一整年,在推出Blackwell GPU之前,可能會略微提高利潤率。
根據庫馬爾的說法,今年晚些時候布萊克韋爾GPU的推出可能會反映出Hopper面臨的供需挑戰。
由於預期的供應限制,客戶不願將訂單從Hopper轉移到Blackwell,他們擔心等待時間會更長。
庫馬爾說,Nvidia的管理層解決了對即將到來的數據中心電力需求的擔憂,他們保證他們的加速計算解決方案比傳統計算更節能。
已經制定了優化未來數據中心的電力需求的計劃,包括利用特定地區的 “滯留電力”,以及考慮在能夠滿足這些重大電力需求的國家設立新的數據中心。
他說,定價討論集中在Nvidia爲其客戶提供的總擁有成本(TCO)優勢上,這表明隨着Blackwell架構的引入,定價理念沒有改變。
儘管該公司的目標是保持有競爭力的定價,但隨着價格的提高,Blackwell架構的毛利率可能會略低於公司平均水平。
根據庫馬爾的說法,Nvidia目前正在實現向主權實體出售數據中心產品的收入機會,預計這一需求將在短期內爲公司的收入做出重大貢獻。
向液冷系統的轉變,尤其是 GB200,是另一個創新領域,主要的雲服務提供商承諾採用 GB200,主要用於推理應用。
在估值方面,英偉達的股票交易價格與同行相比處於溢價,這反映了Nvidia在GPU市場的持續領導地位和創新。
庫馬爾預計第一季度收入和每股收益爲240.1億美元和5.41美元。
瑞穗分析師維傑·拉克什在接待了一位關於數據中心和人工智能供應鏈的行業專家後,指出了英偉達領先的人工智能GPU具有強大的軟件護城河。他還表示,Nvidia是領先的人工智能加速器,尤其是在訓練方面。
英偉達仍然是人工智能的領導者,H100和H200一直處於緊張狀態。根據分析師的說法,布萊克韋爾B100定於2024年推出,並於2025年上市。
但是,他還指出了採用機架供電和冷卻解決方案的新型大功率 Nvidia 系統面臨的一些潛在挑戰,這是數據中心面臨的主要挑戰。
免責聲明:此內容部分是在人工智能工具的幫助下製作的,並由Benzinga的編輯審閱和發佈。