Nvidia Crushes Fourth-Quarter Sales, Earnings Targets, Guides Higher

Release time：2018-02-09
author：Ameya360
source：investors
reading：2624

　　Graphics-chip maker Nvidia (NVDA) late Thursday smashed Wall Street's estimates for its fiscal fourth quarter and guided higher for the current quarter, sending its stock up sharply in extended trading.

　　Nvidia reported earnings per share of $1.78, up 80% year over year, on sales of $2.91 billion, up 34%, in the quarter ended Jan. 28. Analysts expected earnings of $1.16 a share on sales of $2.67 billion for the January quarter, according to Zacks Investment Research.

　　Nvidia shares surged 11% in after-hours trading on the stock market today. During the regular session, Nvidia fell 4.9% to 217.52.

　　For the current quarter, Nvidia expects revenue of $2.9 billion, up 33% year over year. It did not give a target for earnings per share. Nvidia expects its GAAP gross profit margin to be 62.7% in the first quarter, compared with 61.9% in the fourth quarter.

　　Wall Street was modeling Nvidia to earn 97 cents a share, up 18%, on sales of $2.44 billion, up 26%, for the April period, according to Zacks.

　　Nvidia is best known for making graphics processors for PCs and gaming consoles, but has a fast-growing business selling processors for cloud data centers, artificial intelligence applications and self-driving cars. Lately its processors have been used for mining cryptocurrency such as Bitcoin and Ethereum.

　　IBD'S TAKE: Nvidia is ranked No. 8 on the IBD 50 list of top-performing growth stocks.

　　"In a powerful sign of our progress, attendees at Nvidia's GPU Technology Conferences reached 22,000, up 10-fold in five years, as software developers working in AI, self-driving cars, and a broad range of other fields continued to discover the acceleration and money-saving benefits of our GPU computing platform," Nvidia Chief Executive Jensen Huang said in a news release.

　　Huang touted the company's graphics processing units for use in artificial intelligence applications.

　　"Industries around the world are racing to incorporate AI," he said. "Virtually every internet and cloud service provider has embraced our Volta GPUs. Hundreds of transportation companies are using our Nvidia Drive platform. From manufacturing and health care to smart cities, innovators are using our platform to invent the future."

（"Note: The information presented in this article is gathered from the internet and is provided as a reference for educational purposes. It does not signify the endorsement or standpoint of our website. If you find any content that violates copyright or intellectual property rights, please inform us for prompt removal."）

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NVIDIA Enters PC Market with RTX Spark Featuring MediaTek-Co-Designed N1X CPU on TSMC 3nm
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NVIDIA Enters PC Market with RTX Spark Featuring MediaTek-Co-Designed N1X CPU on TSMC 3nm

　　As traditional CPU leaders such as Intel push further into the AI accelerator market, NVIDIA is moving in the opposite direction—leveraging its dominance in AI computing to expand into the PC processor arena. At GTC Taipei on June 1, CEO Jensen Huang unveiled the NVIDIA RTX Spark, developed in partnership with Microsoft and powered by the new Arm-based N1X processor co-designed with MediaTek, according to NVIDIA and CNBC.　　According to CNBC, the initial rollout will include more than 30 notebook models and 10 desktop systems. RTX Spark-powered devices from Microsoft, Dell, HP, ASUS, Lenovo, and MSI are expected to debut this fall, marking NVIDIA’s first large-scale push into the Windows PC CPU market.　　CNBC adds that the platform combines NVIDIA’s Blackwell GPU architecture with the N1X CPU and 128GB of unified memory, bringing data center-class AI capabilities to personal computers. Notably, the new PC processor will be manufactured using TSMC’s 3nm process, which is currently produced exclusively in Taiwan, according to CNBC.　　More Spec Details　　Interestingly, as noted by The Verge, the flagship RTX Spark mirrors the DGX Spark almost exactly — 20 CPU cores, 6,144 GPU cores, 128GB of LPDDR5X memory — though NVIDIA plans to release leaner, more affordable variants, with some configurations dropping to just 16GB of RAM.　　Meanwhile, NVIDIA has provided additional details on the platform’s performance. According to The Verge, with up to 128GB of unified memory—on par with AMD’s previous-generation Strix Halo—RTX Spark laptops and desktops are also capable of hosting AI agents with up to 120 billion parameters, a capability Microsoft appears eager to integrate into Windows.　　Powered by RTX Spark, NVIDIA claims the system can render a 90GB 3D scene, edit 12K video, or run graphically intensive titles like Indiana Jones and the Great Circle at a smooth 100fps in 1440p—all within a 14mm-thin laptop operating without being plugged into power, the report adds.　　CNBC, citing an NVIDIA spokesperson, reports that RTX Spark is described as being “roughly equivalent” to the company’s flagship RTX 5070 laptop GPU.　　NVIDIA is certainly not the only player eyeing to expand its CPU footprint. As noted by CNBC, Apple now designs its own Arm-based processors for Mac computers, having rolled out a higher-end MacBook lineup powered by its latest M5 chips in March. In the same month, Arm unveiled its first in-house CPU, with Meta reportedly serving as the launch customer for the Arm AGI CPU, according to TechCrunch.
2026-06-02 10:29 reading：212
NVIDIA Reportedly Plans GPU-Direct Storage for Vera Rubin, Raising Expectations for HBF Beyond HBM
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NVIDIA Reportedly Plans GPU-Direct Storage for Vera Rubin, Raising Expectations for HBF Beyond HBM

　　As AI models continue to scale, HBM may struggle to meet future memory-capacity demands, prompting industry experts to view GPU-driven storage architectures as a potential next frontier. According to The Elec, NVIDIA and Amazon are reportedly advancing storage architectures that allow GPUs to directly control storage devices such as SSDs. NVIDIA is said to plan the introduction of GPU-Initiated Direct Storage Access (GIDS) starting with its Vera Rubin AI platform, a shift that could accelerate the emergence of high-bandwidth flash (HBF), the report notes.　　Citing Song Ki-hwan, a professor in the Department of System Semiconductor Engineering at Yonsei University, the report explains that GIDS goes beyond existing GPU Direct Storage (GDS) architecture. Under GDS, CPUs issue data requests to storage devices before data is transferred to GPUs. GIDS advances this by allowing GPUs to access storage directly, bypassing CPUs and DRAM.　　Both GIDS and GDS aim to overcome data-transfer bottlenecks tied to traditional von Neumann computing architectures. Microsoft and AMD are also said to be exploring similar approaches. The report, citing Song, adds that traditional data-transfer methods are inefficient because CPUs are structurally limited in thread processing, while GPUs can generate tens of thousands of parallel threads. Song also notes that GPU-HBM data transfer already accounts for roughly half of total system power, strengthening the case for HBF architectures that place ultra-fast NAND closer to GPUs to address future AI bottlenecks.　　GIDS Could Accelerate HBF and Expand NAND’s Role in AI Memory　　The emergence of GIDS could allow NAND storage to take on a larger role in AI memory systems while easing pressure on HBM capacity. As the report notes, this shift would require higher-performance NAND flash capable of keeping pace with GPU processing speeds. One proposed approach is high-bandwidth flash (HBF), which stacks NAND flash vertically in a structure similar to HBM and connects it using through-silicon vias (TSVs).　　The report notes that NAND flash offers roughly 30 times higher bit density than DRAM, enabling far greater memory capacity in a similar footprint. According to Song, combining six HBF units with two HBM units could increase GPU memory capacity more than 16 times, from 192GB to 3,120GB, potentially supporting AI models with parameter sizes around 16 times larger than current architectures.　　Still, NAND flash has endurance limits, typically supporting only around 100,000 write-and-erase cycles versus DRAM’s near-unlimited write capability. As a result, HBF is seen as better suited for storing AI model parameters, which remain largely unchanged during inference and function as read-only workloads.　　Meanwhile, memory makers have also been exploring GPU-driven memory architectures. According to an Edaily report last year, sources said Samsung Electronics is actively researching next-generation high-performance Z-NAND. The company is also developing GIDS technology that would allow GPUs to directly access Z-NAND-based storage devices. If implemented, GPUs would be able to access Z-NAND devices without intermediaries, potentially shortening processing times for AI workloads.
2026-05-20 11:20 reading：814
NVIDIA Confirms Development of “Compliance Chips” for the Chinese Market
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NVIDIA Confirms Development of “Compliance Chips” for the Chinese Market

　　According to IJIWEI’s report, NVIDIA recently confirmed that it is actively working on new “compliant chips” tailored for the Chinese market. However, these products are not expected to make a substantial contribution to fourth-quarter revenue.　　On November 21, during NVIDIA’s earnings briefing for the third quarter of 2024, executives acknowledged the significant impact of tightened U.S. export controls on AI. They anticipated a significant decline in data center revenue from China and other affected countries/regions in the fourth quarter. The controls were noted to have a clear negative impact on NVIDIA’s business in China, and this effect is expected to persist in the long term.　　NVIDIA’s Chief Financial Officer, Colette Kress, also noted that the company anticipates a significant decline in sales in China and the Middle East during the fourth quarter of the 2024 fiscal year. However, she expressed confidence that robust growth in other regions would be sufficient to offset this decline.　　Kress mentioned that NVIDIA is collaborating with some customers in China and the Middle East to obtain U.S. government approval for selling high-performance products. Simultaneously, NVIDIA is attempting to develop new data center products that comply with U.S. government policies and do not require licenses. However, the impact of these products on fourth-quarter sales is not expected to materialize immediately.　　Previous reports suggested that NVIDIA has developed the latest series of computational chips, including HGX H20, L20 PCIe, and L2 PCIe, specifically designed for the Chinese market. These chips are modified versions of H100, ensuring compliance with relevant U.S. regulations.　　As of now, Chinese domestic manufacturers have not received samples of H20, and they may not be available until the end of this month or mid-next month at the earliest. IJIWEI’s report has indicated that insiders have revealed the possibility of further policy modifications by the U.S., a factor that NVIDIA is likely taking into consideration.
2023-11-23 13:24 reading：4002
Ameya360：Quest Global and NVIDIA to Develop Digital Twin Solutions for Manufacturing Industry
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Ameya360：Quest Global and NVIDIA to Develop Digital Twin Solutions for Manufacturing Industry

　　Quest Global is developing new services and solutions, based on the NVIDIA Omniverse Enterprise platform, to deliver the best 3D visualization, simulation, design collaboration, and digital twin solutions for the manufacturing and automotive industries.　　Through this association, Quest Global aims to facilitate the transformation of the traditional manufacturing processes and facilities by enabling manufacturers to augment their physical production environments with large-scale, AI and IoT-enabled, digital twin counterparts. These digital twins will enable manufacturers to optimize their manufacturing, logistics, and warehouse processes, reduce waste, and unlock operational efficiencies.　　“As organizations work towards enabling their manufacturing operations with predictive analysis, operational efficiencies, and innovative automation, live digital twins of factory solutions play a vital role in achieving that. We are proud to work with NVIDIA to set up an Omniverse center of excellence, with trained engineers and NVIDIA-specific labs and infrastructure. This association is a testament to our commitment towards helping our customers pursue the next frontier of innovation and solve the world’s hardest engineering problems,” said Dushyant Reddy, Global Business Head for Hi-Tech, Quest Global.　　NVIDIA Omniverse Enterprise is an end-to-end 3D simulation platform that helps organizations develop and operate physically accurate, perfectly synchronized and AI-enabled digital twins. Building the factories of the future requires uniting disparate datasets from many 3D digital content creation (DCC) and simulation applications in full fidelity, a capability uniquely enabled by Omniverse Enterprise, then connecting to scalable AI platforms such as NVIDIA Isaac Sim for robotics simulation and Metropolis for vision AI applications.　　“The industrial metaverse requires innovative simulation and AI capabilities to tackle today’s critical manufacturing and automotive challenges,” said Brian Harrison, Senior Director of Product Management for Omniverse Digital Twins at NVIDIA. “The collaboration between Quest Global and NVIDIA delivers workflow solutions and enhancements that take manufacturing and design collaboration to the next level.”　　Quest Global — a long-standing Elite member of the NVIDIA Partner Network – is uniquely positioned to leverage its 3D simulation, engineering, and AI capabilities to help manufacturers quickly develop and harness digital twins of their production environments. The company plans to utilize the capabilities of Omniverse for its customers across industry sectors for product design, optimization and operation of factories of the future, simulation and training of robotics, synthetic data generation for AI training and much more.
2023-02-03 11:44 reading：4565
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