NVIDIA Announces Financial Results for Second Quarter Fiscal 2024


Non-GAAP
($ in millions, except earnings
per share)
Q2 FY24 Q1 FY24 Q2 FY23 Q/Q Y/Y
Revenue$13,507 $7,192 $6,704 Up 88%Up 101%
Gross margin 71.2% 66.8% 45.9%Up 4.4 ptsUp 25.3 pts
Operating expenses$1,838 $1,750 $1,749 Up 5%Up 5%
Operating income$7,776 $3,052 $1,325 Up 155%Up 487%
Net income$6,740 $2,713 $1,292 Up 148%Up 422%
Diluted earnings per share$2.70 $1.09 $0.51 Up 148%Up 429%

Outlook
NVIDIA’s outlook for the third quarter of fiscal 2024 is as follows:

  • Revenue is expected to be $16.00 billion, plus or minus 2%.
  • GAAP and non-GAAP gross margins are expected to be 71.5% and 72.5%, respectively, plus or minus 50 basis points.
  • GAAP and non-GAAP operating expenses are expected to be approximately $2.95 billion and $2.00 billion, respectively.
  • GAAP and non-GAAP other income and expense are expected to be an income of approximately $100 million, excluding gains and losses from non-affiliated investments.
  • GAAP and non-GAAP tax rates are expected to be 14.5%, plus or minus 1%, excluding any discrete items.

Highlights

NVIDIA achieved progress since its previous earnings announcement in these areas: 

Data Center

  • Second-quarter revenue was a record $10.32 billion, up 141% from the previous quarter and up 171% from a year ago.
  • Announced that the NVIDIA® GH200 Grace™ Hopper™ Superchip for complex AI and HPC workloads is shipping this quarter, with a second-generation version with HBM3e memory expected to ship in Q2 of calendar 2024.
  • Announced the NVIDIA L40S GPU — a universal data center processor designed to accelerate the most compute-intensive applications — available from leading server makers in a broad range of platforms, including NVIDIA OVX™ and NVIDIA AI-ready servers with NVIDIA BlueField® DPUs, beginning this quarter.
  • Unveiled NVIDIA MGX ™, a server reference design available this quarter that lets system makers quickly and cost-effectively build more than 100 server variations for AI, HPC and NVIDIA Omniverse™ applications.
  • Announced  NVIDIA Spectrum-X™ , an accelerated networking platform designed to improve the performance and efficiency of Ethernet-based AI clouds, which is shipping this quarter.
  • Joined with global system makers to announce new NVIDIA RTX™ workstations with up to four new NVIDIA RTX 6000 Ada GPUs, as well as NVIDIA AI Enterprise and NVIDIA Omniverse Enterprise software, expected to ship this quarter.
  • Launched general availability of cloud instances based on NVIDIA H100 Tensor Core GPUs with Amazon Web Services , Microsoft Azure and regional cloud service providers.
  • Partnered with a range of companies on AI initiatives, including: 
    • ServiceNow and Accenture  to develop AI Lighthouse, a first-of-its-kind program to fast-track the development and adoption of enterprise generative AI capabilities.
    • VMware to extend the companies’ strategic partnership to ready enterprises running VMware’s cloud infrastructure for the era of generative AI with VMware Private AI Foundation with NVIDIA.
    • Snowflake to provide businesses with an accelerated path to create customized generative AI applications using their own proprietary data.
    • WPP to develop a generative AI-enabled content engine that lets creative teams produce high-quality commercial content faster, more efficiently and at scale while staying fully aligned with a client’s brand.
    • SoftBank to create a platform for generative AI and 5G/6G applications based on the GH200, which SoftBank plans to roll out at new, distributed AI data centers across Japan.
    • Hugging Face to give developers access to NVIDIA DGX™ Cloud AI supercomputing within the Hugging Face platform to train and tune advanced AI models.
  • Announced NVIDIA AI Workbench , an easy-to-use toolkit allowing developers to quickly create, test and customize pretrained generative AI models on a PC or workstation and then scale them, as well as NVIDIA AI Enterprise 4.0 , the latest version of its enterprise software.
  • Set records in the latest MLPerf training benchmarks with H100 GPUs, excelling in a new measure for generative AI. 

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