Nvidia Pursues Acquisition of Open

Nvidia, the world's largest company by market capitalization, has made massive investments over the past two years to expand the AI ecosystem and ensure it remains at the center. While the company has its own open-source AI model called "Nemotron," it lacks a frontier-grade proprietary model. Observers suggest the Reflection AI acquisition could fill this gap.

Japanese companies and research institutions are also deeply embedded in Nvidia's open model ecosystem. SoftBank subsidiary SB Intuitions has used Nvidia's training libraries to train its Japanese generative AI "Sarashina" series, while NTT Data has used Nvidia's Japanese persona datasets to expand training data for its "tsuzumi 2" model. Sakana AI has integrated Nemotron into its model routing platform "Fugu," and the Institute of Science Tokyo has developed the "Swallow" series of open models with enhanced Japanese performance using Nemotron datasets. If Nvidia secures a frontier-grade open model through Reflection AI, it is expected to have ripple effects on Japanese companies that have built their models on this ecosystem.

Nvidia has been particularly focused on open-source AI models in recent months. Open-source models allow enterprises to run AI on their own hardware at far lower costs compared to closed models like OpenAI's ChatGPT or Anthropic's Claude. As China's Moonshot, Qwen, and DeepSeek have grown rapidly in this space, the need for a self-sustaining open-source ecosystem within the United States has become increasingly apparent.

Jensen Huang, Nvidia's CEO, emphasized in July this year that the U.S. must build a self-sustaining open-source ecosystem, calling it essential for "creating opportunities for innovation and prosperity across America."

Nvidia's investment strategy is focused on expanding the AI ecosystem to generate demand for its own chips. Beyond major AI startups like OpenAI and Anthropic, the company has invested tens of billions of dollars in neocloud providers including Nebius, CoreWeave, IREN, Lambda, and Nscale. It also holds stakes in optical and photonics companies Coherent and Lumentum, as well as SoundHound, Arm Holdings, and Marvell Technologies.

Nvidia held $99.9 billion in cash and short-term investments as of the end of last quarter, providing ample resources to support large-scale M&A activity. However, the cost burden associated with Reflection AI's business expansion is also substantial. Reflection AI pays SpaceX $150 million per month under a total $6.3 billion computing contract running from July 2026 through 2029, with access to Nvidia GB300 chips at the Colossus 2 data center. The company has also signed a computing contract exceeding $1 billion with Nebius and agreed to co-build a 250MW AI data center with Shinsegae Group.

If the acquisition talks succeed, the deal is expected to have significant implications for the global AI market landscape. Should Nvidia directly acquire open-source AI model development capabilities, its vertical integration—combining its chips with AI models—could strengthen considerably. This could also introduce new tensions in Nvidia's relationships with existing customers like OpenAI and Anthropic, which rely on Nvidia chips while developing their own models.

The deal is also intertwined with the U.S. government's AI competition strategy against China. As the Trump administration works to counter the spread of low-cost Chinese AI models like DeepSeek, Reflection AI's potential emergence as the standard-bearer for a U.S.-led open-source AI ecosystem carries growing geopolitical significance.

From a regulatory standpoint, the acqui-hire approach offers the advantage of avoiding antitrust review, but the possibility remains that regulators could raise concerns over whether Nvidia would exercise de facto control. While Nvidia has precedent from its Groq acquisition, observers note that given Reflection AI's strategic importance and valuation scale, regulatory scrutiny is likely to be more intense.