Company Reports

Nvidia formally announced the acquisition of Hugging Face, a large language model platform, for $12.9 billion. Nvidia intends to support and scale up Hugging Face to continue to serve LLMs, including open-source models.

Nvidia reported fiscal second-quarter revenue of $96 billion, up 106% year over year and ahead of guidance of $91 billion. Nvidia expects October-quarter revenue of $108 billion, up 89% year over year and ahead of FactSet consensus estimates of $105 billion.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, hardware, software, and networking tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will, at best, only chip away at Nvidia’s AI dominance.

Nvidia on Aug. 10 announced strategic partnerships with six large financial institutions to “establish AI compute infrastructure financing platforms … to mobilize over $500 billion of third-party capital” for use in artificial intelligence buildouts.

The Wall Street Journal reported that Nvidia is in discussions to provide a roughly $250 billion backstop for OpenAI as part of a massive data center project in Ohio. The report suggests that the backstop will allow OpenAI, still a privately owned startup, to receive better financing terms.

At Computex 2026, Nvidia’s keynote address noted that its Vera Rubin artificial intelligence rack-scale solutions are ramping into full production. It announced the RTX Spark “superchip” that combines a Blackwell graphics processor (GPU) and N1X/N1 processor (CPU) for PCs in the agentic AI era.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, hardware, software, and networking tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will, at best, only chip away at Nvidia’s AI dominance.

Nvidia reported fiscal first-quarter revenue of $81.6 billion, up 85% year over year and ahead of guidance of $78 billion. Nvidia expects April-quarter revenue of $91 billion, up 95% year over year and ahead of the FactSet consensus estimate of $87.2 billion.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, hardware, software, and networking tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will, at best, only chip away at Nvidia’s AI dominance.

Nvidia hosted its annual GTC conference and gave an outlook of $1 trillion of cumulative revenue from Blackwell and Rubin AI products from 2025-27. They also announced low-latency processors from their recent license with Groq, and NemoClaw to support OpenClaw "agentic" artificial intelligence.

Nvidia will invest $30 billion in OpenAI as part of OpenAI’s $110 billion financing round at a $730 billion pre-money valuation. OpenAI will use 3 gigawatts of dedicated inference capacity, along with 2 GW of AI training on Nvidia’s latest Vera Rubin systems.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, hardware, software, and networking tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will, at best, only chip away at Nvidia’s AI dominance.

Nvidia reported fiscal fourth-quarter revenue of $68.1 billion, up 73% year over year, up 20% sequentially, and ahead of guidance. Nvidia expects April-quarter revenue of $78.0 billion, which would be up 77% year over year and ahead of FactSet consensus estimates of $72.9 billion.

Nvidia touted its lineup of product innovations at a keynote address at CES 2026 in Las Vegas and hosted a question-and-answer session with financial analysts. The firm’s artificial intelligence roadmap remains on track, with its Vera Rubin products coming to market in the second half of 2026.

In a Dec. 8 Truth Social post, US President Donald Trump said the US will allow Nvidia to sell its roughly two-year-old artificial intelligence graphics processors, or GPUs, the H200, into China. The US government will reportedly receive a 25% cut on all sales, versus prior discussions of a 15% cut.

The Information reported that Meta Platforms is in discussions to buy Google’s custom Tensor Processing Unit, or TPU, chips for artificial intelligence. Shares of AI chip suppliers Nvidia and AMD were down as much as 4% and 7%, respectively, on Nov. 25.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, hardware, software, and networking tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will, at best, only chip away at Nvidia’s AI dominance.

Nvidia reported fiscal third-quarter revenue of $57 billion, up 22% sequentially, up 62% year over year, and ahead of guidance of $54 billion. Nvidia’s forecast for the January quarter of $65 billion would be ahead of the FactSet consensus estimate of $62 billion and be up 65% year over year.

Nvidia hosted its GTC conference in Washington, D.C. and touted a variety of its product announcements. Nvidia disclosed that, to date, it has visibility into $0.5 trillion of cumulative revenue for its Blackwell and Rubin products in calendar 2025 and 2026.

Nvidia has a wide economic moat, thanks to its market leadership in graphics processing units, or GPUs, hardware, software, and networking tools needed to enable the exponentially growing market around artificial intelligence. In the long run, we expect tech titans to strive to find second-sources or in-house solutions to diversify away from Nvidia in AI, but these efforts will, at best, only chip away at, but not supplant, Nvidia’s AI dominance.