Nvidia has bet on open source in the race for global AI leadership. According to my data, the company has signed a $6 billion deal with the American startup Poolside to develop a powerful open-weights model capable of directly competing with Chinese large language models (LLMs), including DeepSeek and Kimi K3 from Moonshot AI.
Deal structure and strategic context
The partnership terms involve a $6 billion payment for licenses to Poolside's AI models, the hiring of more than 100 startup employees, and additional investments of $1 billion. This deal structurally mirrors the recent acquisition of chip developer Groq, where Nvidia paid $20 billion for licenses and integrated most of the specialists and founders into its team. This approach points to a systematic strategy: Nvidia is not just buying technology but absorbing talent and intellectual property to accelerate its own development.
The race for open models
The key motive is democratizing access to AI. Nvidia consistently supports open-weight models that developers can freely use and adapt. This not only reduces the market's dependence on a few closed giants like OpenAI and Anthropic but also stimulates demand for Nvidia's own chips and AI systems. Open-weights models are significantly cheaper to operate and easier to customize, making them an attractive alternative for businesses.
Political backdrop and pressure on China
The intensifying competition comes amid renewed discussions in Donald Trump's administration about possible restrictions on the use of Chinese open-weight models. In July, 25 American companies, including Nvidia, Meta, and Microsoft, issued an open letter warning that bans would not strengthen U.S. technological leadership but would merely shift the market toward closed developers. The release of Kimi K3, whose creators the White House accused of distilling Anthropic's Fable model, served as the trigger for heightened debates.
My assessment: this deal is not just a response to the Chinese challenge but an attempt by Nvidia to reshape the entire AI market according to its own standards. By investing in open models, the company is creating an ecosystem where its hardware becomes indispensable, and competitors are forced to play by its rules. If the strategy works, we will see market consolidation around open standards, which in the long term could weaken the positions of closed monopolists.