NVIDIA reports $44.06B in Q1 FY26, amid a $4.5B H20-related loss and expanding AI infrastructure across the U.S. and Asia. This marks a 69% increase year-over-year and a 12% rise quarter-over-quarter, demonstrating that export restrictions and the company’s recent share price volatility have not diminished its critical role in powering compute infrastructure across essential industries such as AI and Crypto.
Margins and Profitability of Nvidia – Growth of Indicators Even Amid Certain Constraints and Losses
As we already said, the company announced record revenue of $44.06 billion, 69% higher compared to the same period last year and 12% higher quarter-over-quarter – the main contribution to which came from the Data Center segment, which delivered $39.1 billion. This is as much as 73% more than a year earlier, confirming that such compute-intensive areas as AI and crypto are still not just going strong but gaining momentum.
However, this race also has a downside, causing regulatory tightening, so the company recognized losses from export restrictions on H20. The result of this was a $4.5 billion write-down on inventory and obligations, as well as the inability to deliver another $2.5 billion during the reporting period.
Gross margin under GAAP fell to 60.5% (from 73% in the previous quarter), and under non-GAAP to 61% – again, without accounting for H20-related losses, this figure would have been 71.3%, comparable to the company’s target range.
Earnings per share amounted to $0.76 under GAAP and $0.81 under non-GAAP, and if the impact of export restrictions is excluded, the adjusted figure would have been $0.96, which is 60% higher than the same period of FY25.
Data Center Segment – Focus on Localized Capacity and AI Infrastructure
Among other indicators, this one is indeed the most important and may point to the industry’s trajectory. In response to restrictions, NVIDIA accelerated the construction of its own AI factories. For example, in the US, production of Blackwell supercomputers has already begun, projects in Taiwan jointly with Foxconn have been confirmed, in Saudi Arabia with HUMAIN, and also in the UAE through Stargate UAE – a next-generation cluster in partnership with G42, OpenAI, Oracle, SoftBank, and Cisco.
All this forms the computing foundation not only for centralized solutions but also for independent clouds, edge instances, and systems with sovereign infrastructure requirements, which is critical for independent developments in the field of AI and decentralized financial systems.
Speaking broadly, NVIDIA infrastructure and the architectures Blackwell, Grace Hopper, and DGX today de facto play a crucial role in a number of decentralized ecosystems – in particular, in the projects io.net, Bittensor, Akash, Gensyn, and are used for proof calculations, on-chain inference, and AI-agent orchestration.
Gaming Segment – 48% Growth and Continued DLSS 4 Expansion
Gaming, until recently, was the only driver behind the development of more efficient and high-performance solutions, but it still plays its role. It delivered revenue of $3.8 billion, 48% more than in the previous quarter and 42% higher year-over-year. Naturally, this is mainly due to new products like RTX 5070 and RTX 5060, the appearance of DLSS 4 in more than 125 games, and confirmation that the Nintendo Switch 2 uses an NVIDIA chip.
This, by the way, is also important for Web3 infrastructure, where similar solutions are assembled into clusters and also become powerful blockchain nodes. In addition, this expands options and makes possible Web3 metaverses with visual layers generated off-chain with subsequent on-chain verification of ownership rights and authenticity.
Robotics, Professional Visualization, Digital Twins, and Other Advanced Trends Gain Resilience
The company introduced the open-source platform Isaac GROOT N1, the first architecture for humanoid robots supporting agentic reasoning and motion generation based on Blackwell. Another very important thing was the launch of the Halos safety system and the Isaac Cosmos models, designed for edge computing in transportation and industrial scenarios with integrations based on Omniverse and the Cosmos SDK.
By the way, regarding this, an extremely interesting – in my opinion – point was the revenue in the professional visualization segment: $509 million, a 19% year-over-year increase thanks to RTX PRO Blackwell workstations, DGX Spark, and integrations with SAP, Siemens, Schneider Electric, and Accenture. The Omniverse platform is becoming the foundation here for digital twins, industrial simulation, and enterprise-level 3D model generation – all this is powered by Nvidia hardware.
The integration of this with Web3 protocols in the field of spatial modeling, where the object registry (NFTs, DAO contracts, simulations) can be linked with digital twins and on-chain scenarios in metaverses, as I see it, is only a matter of time.
Forecast for Q2 FY26 – Loss Neutralization and Return to Margin Growth
For the second quarter, the company forecasts revenue of $45 billion with a deviation of ±2%, while the loss of approximately $8 billion in potential revenue due to H20 restrictions has already been accounted for in the calculations. NVIDIA expects gross margin to recover to the level of 71.8%–72.0% and total operating expenses to be $5.7 billion with an expected effective tax rate of 16.5% ±1%. The next dividend of $0.01 per share will be paid on July 3, 2025.
Conclusion
What can we conclude and assume from this report? First of all, Nvidia increasingly follows Apple’s approach, moving away from pure hardware and transforming into a software-hardware complex, but at a corporate and government grade.
We also observe how the focus is shifting toward high-performance, high-efficiency, yet flexible solutions, primarily for the needs of AI, robotics, and similar sectors. However, decentralized financial systems and cryptocurrencies are making excellent use of these capacities, and their strategic role is also growing at the national level, which is good news for the crypto industry.
In the end, we get more powerful and efficient hardware, meaning cheaper computational operations and favorable conditions for the crypto market – all this without taking major risks in the face of volatility, as long as the main focus remains on AI.
