With GAAP gross revenue up 7% year-on-year (topping $5bn) and margins also improved, it’s another set of bumper results for the Santa Clara-based GPU architects.
With GAAP gross revenue up 7% year-on-year (topping $5bn) and margins also improved, it’s another set of bumper results for the Santa Clara-based GPU architects.
PRESS RELEASE18.02.2016 – NVIDIA (NASDAQ: NVDA) today reported record revenue for the fourth quarter ended January 31, 2016, of $1.40 billion, up 12 percent from $1.25 billion a year earlier, and up 7 percent from $1.30 billion in the previous quarter. Revenue for fiscal 2016 was a record $5.01 billion, up 7 percent from $4.68 billion a year earlier. GAAP earnings per diluted share for the quarter were $0.35, inclusive of a restructuring charge of $0.04 per diluted share. Non-GAAP earnings per diluted share were $0.52, up 21 percent from $0.43 a year earlier and up 13 percent from $0.46 in the previous quarter.
GAAP earnings per diluted share for the full year were $1.08, inclusive of restructuring charges of $0.15 per diluted share. Non-GAAP earnings per diluted share were $1.67, up 18 percent from $1.42 a year earlier. “We had another record quarter, capping a record year,” said Jen-Hsun Huang, co-founder and chief executive officer, NVIDIA. “Our strategy is to create specialized accelerated computing platforms for large growth markets that demand the 10x boost in performance we offer. Each platform leverages our focused investment in building the world’s most advanced GPU technology.
“NVIDIA is at the center of four exciting growth opportunities — PC gaming, VR, deep learning, and self-driving cars. We are especially excited about deep learning, a breakthrough in artificial intelligence algorithms that takes advantage of our GPU’s ability to process data simultaneously. “Deep learning is a new computing model that teaches computers to find patterns and make predictions, extracting powerful insights from massive quantities of data. We are working with thousands of companies that are applying the power of deep learning in fields ranging from life sciences and financial services to the Internet of Things,” he said.
Capital Return
During the fourth quarter, NVIDIA paid $62 million in cash dividends and received 4.3 million shares in connection with an accelerated share repurchase agreement that it had entered into in the quarter. During fiscal 2016, the company returned to shareholders $800 million in quarterly cash dividends and share repurchases. For fiscal 2017, NVIDIA intends to return approximately $1.0 billion to shareholders through ongoing quarterly cash dividends and share repurchases. NVIDIA will pay its next quarterly cash dividend of $0.115 per share on March 23, 2016, to all shareholders of record on March 2, 2016.
Q4 FY2016 Summary
FY2016 Summary
NVIDIA’s outlook for the first quarter of fiscal 2017 is as follows:
Revenue is expected to be $1.26 billion, plus or minus two percent.
GAAP and non-GAAP gross margins are expected to be 57.2 percent and 57.5 percent, respectively, plus or minus 50 basis points.
GAAP operating expenses are expected to be approximately $500 million. Non-GAAP operating expenses are expected to be approximately $445 million.
GAAP and non-GAAP tax rates for the first quarter of fiscal 2017 are both expected to be 19 percent, plus or minus one percent.
Capital expenditures are expected to be approximately $35 million to $45 million.
GAAP and non-GAAP gross margins are expected to be 57.2 percent and 57.5 percent, respectively, plus or minus 50 basis points.
GAAP operating expenses are expected to be approximately $500 million. Non-GAAP operating expenses are expected to be approximately $445 million.
GAAP and non-GAAP tax rates for the first quarter of fiscal 2017 are both expected to be 19 percent, plus or minus one percent.
Capital expenditures are expected to be approximately $35 million to $45 million.
Fourth Quarter Fiscal 2016 Highlights
During the fourth quarter, NVIDIA achieved progress in each of its platforms.
Gaming:
Announced the GeForce GTX VR Ready program — in conjunction with PC companies, notebook makers and add-in card providers – to help users discover systems that will provide great virtual reality experiences.
Released NVIDIA GameWorks VR, a software development kit for developers of VR software and headsets for gaming.
Released NVIDIA GameWorks VR, a software development kit for developers of VR software and headsets for gaming.
Professional Visualization:
Rolled out NVIDIA Iray plugins for Autodesk Maya and Autodesk 3ds Max, which enable users of these applications to create designs incorporating real-world lights and materials faster and more easily than before.
Released NVIDIA DesignWorks VR, a software development kit for developers of VR software and headsets for enterprise.
Released NVIDIA DesignWorks VR, a software development kit for developers of VR software and headsets for enterprise.
Datacenter:
Introduced an end-to-end hyperscale datacenter deep learning platform — consisting of two accelerators, the NVIDIA Tesla M40 and NVIDIA Tesla M4 — that lets web-services companies accelerate deep learning workloads.
Revealed new breakthroughs from leading web-services groups using NVIDIA GPUs:
Facebook is using the NVIDIA Tesla accelerated computing platform to power Big Sur, its next-generation computing system for machine learning applications.
Alibaba’s AliCloud cloud computing business is working with NVIDIA to promote China’s first GPU-accelerated, cloud-based, high performance computing platform.
IBM is adding support for NVIDIA GPU accelerators to its Watson cognitive computing platform.
Google is open-sourcing its TensorFlow deep-learning framework, which can be accelerated on GPUs.
Microsoft’s Computational Network Toolkit was integrated with Azure GPU Lab, enabling neural nets for speech recognition that are up to 10x faster than their predecessors.
Alibaba’s AliCloud cloud computing business is working with NVIDIA to promote China’s first GPU-accelerated, cloud-based, high performance computing platform.
IBM is adding support for NVIDIA GPU accelerators to its Watson cognitive computing platform.
Google is open-sourcing its TensorFlow deep-learning framework, which can be accelerated on GPUs.
Microsoft’s Computational Network Toolkit was integrated with Azure GPU Lab, enabling neural nets for speech recognition that are up to 10x faster than their predecessors.
Auto:
Launched NVIDIA DRIVE PX 2, a powerful engine for in-vehicle artificial intelligence.
Announced that Volvo will use DRIVE PX 2 to power a fleet of 100 Volvo XC90 SUVs that will appear on the road next year in the car manufacturer’s Drive Me autonomous-car pilot program.
Announced that Volvo will use DRIVE PX 2 to power a fleet of 100 Volvo XC90 SUVs that will appear on the road next year in the car manufacturer’s Drive Me autonomous-car pilot program.
