Nvidia (NASDAQ:NVDA | NVDA Price Prediction) has been making so many deals and investments that it’s getting harder to keep up. Whether you’re a bull or a bear over every new AI-related deal that Nvidia and Jensen Huang strike, the moves don’t seem to be as much of a mover of the stock anymore. In many ways, it seems like the GPU giant has run into a bit of a brick ceiling while its market cap is hovering around the $4.5 trillion range.
With the latest GTC 2026 conference giving Nvidia shareholders plenty of reason to hold on, I do think that its investment in Thinking Machines Lab is one of the most intriguing deals of the year so far. Of course, we’re just under three months into 2026, yet Nvidia has already made several deals to further enhance its AI growth engine.
It’s getting harder to keep up with every Nvidia deal!
Circular or not, Nvidia’s acquisition spree is gaining momentum, even if its stock is lacking in it. Even if the AI trade picks up negative momentum, my bet is that the deals will keep on coming. If anything, lower ticket prices for the next leaders in AI may actually drive greater spending.
As investors eagerly await the “next ChatGPT” or the ChatGPT for the agentic age (Jensen Huang seems to think that OpenClaw fits the bill as the next ChatGPT), I do think that spreading Nvidia’s many chips across the table could continue to prove a wise bet.
With much of the headlines surrounding Nvidia and its latest $30 billion investment in OpenAI as a part of the ChatGPT maker’s latest funding round, I do think that the stealthier Thinking Machines Lab deal may be at risk of not getting the coverage it deserves. For those unfamiliar with the firm, it’s the AI startup run by former OpenAI CTO Mira Murati.
Thinking Machines Lab has the attention of big tech
Undoubtedly, Thinking Machines Lab has really grabbed the attention of big tech, with Meta Platforms (NASDAQ:META) reportedly interested in buying the startup outright last year. Of course, Mark Zuckerberg are masters of acquiring businesses with explosive potential early on. Still, with Murati reportedly turning down a $1 billion takeover offer, questions linger as to where the mysterious up-and-comer is headed next and how much it could be worth (a $12 billion valuation seems to make more sense after the latest funding round).
In any case, given the tech and talent aboard the startup, Thinking Machines Lab certainly stands out as a serious contender in the AI race, even if the market views it as more of a distant underdog compared to the likes of OpenAI and Anthropic.
Though the magnitude of the Nvidia investment wasn’t disclosed, it is reported to be “significant.” What’s most exciting is the strategic partnership that will see Nvidia provide the 1 GW hardware firepower that Murati’s firm needs to scale. In any case, what separates one frontier model maker from others lies in the approach. For Anthropic, it’s more about going after the enterprise with an efficiency focus.
The unique approach that might just win the AI wars
As for Thinking Machines Lab, the startup seems to be going down the meta-learning angle, which may very well be the way to get around the shortcomings of large language models.
Add the customizable nature of the model, as well as the focus on collaborative AI (the aim appears to be to augment rather than replace), and Thinking Machines Lab certainly stands out as an AI startup that may very well be playing chess while some of its rivals are playing checkers. Could Nvidia really be getting an outstanding bargain at these valuations?
Given the intriguing and responsible approach to developing models, I’d argue there’s a good chance of this. Either way, Thinking Machines Lab’s approach may very well be the model to strive for as AI moves on from LLMs.
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