Bloomberg reported, citing informed sources, that chip giant Nvidia is planning to invest an additional $500 million to $1 billion in AI programming model company Poolside to help it complete a $2 billion round of financing. The financing round valued Poolside at $12 billion before the investment. If the deal is successfully closed, Nvidia's final investment amount could rise to as much as $1 billion, depending on other investors' commitments.

Poolside is headquartered in the United States and Paris, focusing on building large models for software development scenarios. Its tools mainly target code generation, debugging, and automated programming processes, with customers already covering defense and government sectors. Notably, this is not Nvidia's first bet on the company—during Poolside's $500 million Series B funding round in October 2024, Nvidia had already participated, when the company's valuation was only $3 billion, and its valuation is expected to quadruple within a year.

Nvidia has been continuously expanding its investment portfolio in the AI ecosystem in recent years. In addition to Poolside, the company was recently reported to be considering an investment of $500 million in UK autonomous driving company Wayve, and in September, it spent $5 billion to purchase shares in Intel, aiming for future chip collaboration. Combined with previous investments in over 100 AI startups such as Cohere, Runway, and Perplexity, Nvidia has built a complete chain spanning computing power, models, and applications, further securing the rigid demand for its high-end GPUs.

Poolside has already received over $1 billion in investment commitments, with existing shareholders such as Magnetar Capital also continuing to follow up. The final closing is expected to be completed by the end of the year. Neither Nvidia nor Poolside have commented on the details of the transaction, but the market generally believes that this investment will accelerate the deployment of AI-assisted programming tools and reinforce Nvidia's core position in the infrastructure of generative AI.