NVIDIA Corporation develops graphics processing units, accelerated computing systems, and software platforms used in gaming, artificial intelligence, data centers, and AI model development. Company news around NVDA commonly covers financial results, data center demand, AI infrastructure partnerships, networking and optical-connectivity collaborations, and platform launches such as NVIDIA Ising and NVLink Fusion.
Updates also address NVIDIA’s AI factory architecture, systems that connect GPUs for large workloads, quantum-computing tools for calibration and error correction, and governance changes involving the board, audit committee, and executive finance roles.
AWS (NASDAQ: AMZN) and NVIDIA (NASDAQ: NVDA) announced a major expansion of their AI collaboration, with AWS planning to deploy 2 million additional NVIDIA Blackwell Ultra, Rubin and Rubin Ultra GPUs across its global infrastructure in 2027–2028, including AI factories.
The companies plan to build U.S. government AI factories with 100,000 GPUs on secure AWS infrastructure, bring NVIDIA Vera CPU‑based infrastructure to AWS, extend NVLink Fusion with NVHBM, and integrate NVIDIA’s platform with AWS Nitro and EFA. The collaboration also expands support for Nemotron open models, GPU‑accelerated data processing and vector indexing on Amazon EMR and OpenSearch, and advances physical AI for robotics via Amazon Robotics’ adoption of NVIDIA’s Jetson, Omniverse and Isaac platforms.
NVIDIA (NASDAQ: NVDA) reported second quarter fiscal 2027 revenue of $96.2 billion, up 18% sequentially and 106% year over year. GAAP and non-GAAP gross margins were both 75.0%. GAAP diluted EPS was $2.46, while non-GAAP diluted EPS was $2.22.
Data Center revenue reached $89.0 billion, up 18% quarter over quarter and 117% year over year. GAAP operating income was $63.7 billion and GAAP net income was $59.7 billion, increases of 19% and 126% year over year, respectively.
NVIDIA returned about $26.0 billion to shareholders via repurchases and dividends in the quarter and has roughly $99.0 billion remaining under its buyback authorization. The next quarterly cash dividend of $0.25 per share will be paid on October 1, 2026. For Q3 fiscal 2027, NVIDIA expects revenue of $108.0 billion ±2%, gross margin of about 74.0% ±50 bps, and GAAP/non-GAAP operating expenses of approximately $9.2 billion and $9.0 billion, respectively, and is not assuming any Data Center compute revenue from China in this outlook.
NVIDIA (NASDAQ: NVDA) unveiled the Jetson Orin Nano 2, a new entry-level robotics computer for edge AI that targets robots, drones and vision systems. The module delivers 78 trillion operations per second of AI compute, 8GB of memory and an 8-core Arm CPU.
According to NVIDIA, Jetson Orin Nano 2 offers 2x the inference performance of Jetson Orin Nano Super in the same form factor and can use 40% less power at equal performance. Over 3 million developers build on NVIDIA’s robotics stack, with early adopters including Cognex, Doosan Bobcat, Matic and Wing. Partners such as AAEON, ADLINK and Advantech are creating carrier boards and hardware systems. The module and developer kit are expected to be available in the first half of 2027.
NVIDIA (NASDAQ: NVDA) announced that NVIDIA Groq 3 LPX, an interactive AI inference accelerator extending the Vera Rubin NVL72 platform, is now in full production. The product targets agentic AI workloads that require ultrafast token generation across long, multi-step inference sequences.
According to NVIDIA, Groq 3 LPX dramatically increases token generation rates on Vera Rubin NVL72 systems, delivering 3,400 output tokens per second in Artificial Analysis benchmarking on the Gemma 4 31B model with a 100,000-token context, described as the fastest result recorded for this model. NVIDIA also reports up to 4x faster responsiveness for agentic and other latency-sensitive workloads versus the nearest alternative platform.
Nebius will be the first AI cloud to adopt Groq 3 LPX via its Nebius Token Factory production inference platform, with AI cloud provider Groq planning to be among the earliest additional adopters. Groq 3 LPX integrates into NVIDIA’s broader Vera Rubin AI factory architecture alongside BlueField-4 DPUs, Vera CPU racks, storage and Spectrum-6 Ethernet.
NVIDIA (NASDAQ: NVDA) announced that SpaceXAI will deploy NVIDIA Vera CPUs and the Vera Rubin platform to power its next-generation agentic AI infrastructure for Grok, scaling toward gigawatts of compute capacity.
SpaceXAI plans to use Vera to accelerate CPU-intensive orchestration, code execution, data processing and simulations, keeping GPUs fully utilized. NVIDIA Vera features 88 Olympus cores, Spatial Multithreading and LPDDR5X memory delivering up to 1.2TB/s bandwidth, enabling up to 1.8x faster task completion versus x86 CPUs. SpaceXAI also plans a first-generation Starmind AI satellite based on an optimized Vera Rubin NVL72 rack-scale system, extending NVIDIA’s accelerated computing architecture from terrestrial AI factories into orbital AI infrastructure.
NVIDIA (NASDAQ: NVDA) will be the exclusive AI compute infrastructure provider at SB Energy’s PORTS-Pike Technology Campus in Pike County, Ohio, securing land, power and shell capacity to host NVIDIA AI factories. The initial deployment is designed for 4.25 IT-GW of AI factory capacity, with an option on the remaining 3.75 IT-GW for a total of 8 IT-GW.
SB Energy will build, own and operate the data center under a 20-year lease to OpenAI, which will be the customer. NVIDIA will provide credit support on land, power and shell buildout and invest $1.5 billion in SB Energy. The broader project includes at least 10 GW of new energy generation, $4.2 billion in regional grid investment, and an $80 million community benefits fund, with capacity expected to come online in phases beginning in 2028.
NVIDIA (NASDAQ: NVDA) announced strategic partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent AI compute financing platforms intended to mobilize over $500 billion of third-party capital over time for AI infrastructure buildout.
According to NVIDIA, memorandums of understanding with these six financial institutions aim to create dedicated capital pools at significant scale and attractive rates for NVIDIA customers, turning NVIDIA compute and full-stack AI infrastructure into an investable asset class and broadening access to AI factories across its ecosystem. These partnerships remain subject to execution of final agreements.
NVIDIA (NASDAQ: NVDA) will hold a conference call on Wednesday, August 26, 2026, at 2 p.m. PT (5 p.m. ET) to discuss financial results for the second quarter of fiscal year 2027, which ended July 26, 2026.
The listen-only webcast and related materials, including written CFO commentary posted around 1:20 p.m. PT, will be available on investor.nvidia.com, with a replay accessible until the next quarter’s results call.
NVIDIA (NASDAQ:NVDA) and Safe Superintelligence (SSI), led by Ilya Sutskever, announced a long-term strategic partnership under which NVIDIA will both invest in SSI and provide access to its next-generation Vera Rubin compute platform.
According to the companies, NVIDIA’s substantial investment and Vera Rubin access are expected to expand SSI’s compute capacity by roughly an order of magnitude, supporting SSI’s focused effort to develop a safe superintelligent AI system. The partners also plan to collaborate on the technical advancement of NVIDIA’s current and future compute platforms, using SSI’s research insights into the future of AI. NVIDIA said it entered the partnership after gaining rare visibility into SSI’s closely guarded research, while SSI called the Vera Rubin platform a key enabler for scaling its work.
NVIDIA (NASDAQ: NVDA) expanded its NVIDIA Agent Toolkit for engineering by adding re-architected PhysicsNeMo AI physics libraries and updated CUDA-X libraries, giving autonomous AI engineering agents access to AI physics skills, accelerated sparse solvers (cuISS, cuDSS) and quantum chemistry capabilities (cuEST).
The company highlighted Nemotron 3 Ultra, which leads among open models in agentic RTL coding with the ACE-RTL agent. According to NVIDIA, industry leaders including Cadence, Siemens, Synopsys, Samsung, Silvaco, Keysight and TSMC are already using these accelerated computing and agentic AI technologies for workflows spanning chip design, verification, packaging, PCB, 3D-IC, thermal analysis, lithography and quantum chemistry, reporting speedups of up to 20x for multiphysics, over 10x for library characterization and up to 50x for key quantum-chemistry workloads.