Nvidia is in talks to buy Reflection AI, a U.S. AI company it put $800 million into a year ago, or to raise its stake, the Financial Times (FT) reported on Oct. 10. The talks are at an early stage and nothing is final. Reuters said it could not immediately verify the report.
The usual take: deep-pocketed Nvidia is grabbing yet another business. But the real story is elsewhere. BITPRESS sees Nvidia going after a way to grow the number of customers who buy its chips. That goal also lines up with what the U.S. government wants.
Nvidia builds up an open AI company → anyone can download that AI for free → more chips are needed to run it.
- What kind of company is Reflection AI?
Reflection AI was founded in 2024 by two former researchers at Google DeepMind (Google's AI lab). On Oct. 5 it announced Beam, its first "open" AI model. An open (open-weight) model is one whose core files anyone can download and run on their own computers. Beam's files are due out later in October.
Think of it as handing out recipes for free. With a closed AI like ChatGPT, you have to eat at the restaurant. With an open model, you take the recipe and cook at home. But to cook at home, you have to buy your own kitchen equipment.
- Why does a chip company care about AI models?
That kitchen equipment is Nvidia's chips. A company that downloads an open model has to set up its own computers to run it, and the vast majority of that computing runs on Nvidia chips.
According to The Motley Fool, a U.S. investing site, Nvidia CEO Jensen Huang has pointed out that roughly 1 in 4 AI tokens (the word pieces AI produces) already come from open models (as of an Aug. 4 article). Put simply, the more free recipes go around, the busier the kitchen-supply store gets.
- Why an American open model?
The catch: most of the best open models are Chinese. Tech analyst firm RedMonk found that, with rare exceptions such as Nvidia's own Nemotron models, the largest and best-performing open models of 2026 were all Chinese in origin. Beam is competing with lower-cost Chinese models such as DeepSeek and Kimi. Last year even Airbnb CEO Brian Chesky said his company was "relying a lot" on Alibaba's Chinese Qwen model, calling it "fast and cheap."
Reflection CEO Misha Laskin says companies and governments often won't use Chinese models because of possible legal trouble. If a good American open model comes along, those users could become new buyers of Nvidia chips.
The U.S. government is looking the same way. Its July 2025 AI Action Plan (the government's AI policy plan) said the country needs "leading open models founded on American values." A year ago, when Reflection's funding round was announced, White House AI and crypto czar David Sacks wrote: "It's great to see more American open source AI models."
- How much has its value grown?
Reflection was valued at $8 billion in October 2025, about 15 times its $545 million valuation seven months earlier. In that round Nvidia joined a $2 billion investment, putting in $800 million. In April this year, Laskin said the company was raising money at a $25 billion pre-money valuation. Whether a deal closed at that price has not been confirmed.
Put simply, the price the company itself asked for is more than three times what it was worth when Nvidia came in a year ago.
- Why it might not be a full takeover
According to the FT, instead of buying the whole company, a deal could take the form of hiring its staff and licensing its technology. That could let Nvidia avoid a lengthy regulatory review, the FT said. It's like hiring a restaurant's chef and paying to use their recipes instead of buying the building.
A year ago Nvidia was an investor. If these talks end in a purchase or an acqui-hire, it would bring the people and the technology in-house. But the result could also be just more investment, and a deal could come within weeks or fall apart.
- BITPRESS Insight
As BITPRESS sees it, these talks may signal where Nvidia's money is heading. It is not stopping at making and selling chips; it is working to grow the customers who will buy them. As open models spread, Nvidia's customers widen from a handful of big AI companies to countless businesses and governments that download and run those models.
For someone who owns Nvidia stock, whether this deal closes within weeks matters less. What matters is whether Nvidia keeps spending its money on growing the number of chip buyers.
Next time you see news of an Nvidia investment, ask first: "If that company succeeds, will more people use Nvidia chips?"
Sources
https://www.investing.com/news/stock-market-news/nvidia-in-talks-to-invest-further-in-reflection-ai-or-buy-it-ft-reports-4942221
https://www.ft.com/content/052610c5-22b4-4dd4-932e-b7f9f0628b6a
https://seekingalpha.com/news/4651913-nvidia-buy-open-model-startup-reflection-ai
https://techcrunch.com/2025/10/09/reflection-raises-2b-to-be-americas-open-frontier-ai-lab-challenging-deepseek
https://www.opensourceforu.com/2026/07/nvidia-backs-reflection-ai-with-800m-in-pursuit-of-open-weight-ai
https://thehill.com/policy/technology/6130496-reflection-ai-releases-beam-model/amp/
https://www.fool.com/investing/2026/08/04/jensen-huang-push-open-weight-ai-models-nvidia-tam/
https://redmonk.com/sogrady/2026/09/03/open-weight-models/
https://www.whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf
https://www.mt.co.kr/economy/2026/10/08/2026100815360412966
Glossary
Open (open-weight) model — An AI model whose core files are released so anyone can download, run and modify it on their own computers.
Token — The word-piece unit AI uses when reading and writing text, often used to measure how much AI is being used.
Pre-money valuation — A company's value before new investment comes in; add the new money and you get the post-money valuation.
Acqui-hire — A deal in which a company hires another company's key staff and licenses its technology instead of buying the whole company.
BITPRESS articles are information to help your investment decisions, not a recommendation to buy or sell any stock or coin. Investment decisions and their results are your own responsibility.
