The "compute king" of Silicon Valley is making an unprecedented strategic shift, redefining the boundaries of AI inference. On February 27, 2026, according to insiders, NVIDIA plans to launch a new processor specifically tailored for OpenAI and top developers, aiming to create faster and highly efficient AI tools.

This move is seen as a major transformation in NVIDIA's business model—from a general GPU supplier to a deep customization system architect.

Key Highlights: A "nuclear-level" leap in inference performance

NVIDIA is not doing this alone but is incorporating aggressive external technological elements:

Integration of Groq chips: The new system will integrate the ultra-fast chips designed by the Silicon Valley unicorn Groq. Groq is known for its LPU (Language Processing Unit) technology, which has repeatedly set industry records in processing large model inference speed.

Focused on "inference computing": Unlike previous H-series chips that focused on training, this new platform is specifically redesigned for AI inference (the process of a model responding to user requests in real time).

Major announcement scheduled: NVIDIA plans to unveil this new platform at the GTC 2026 Developer Conference in San Jose next month.

Strategic Battle: Holding onto OpenAI, the "top player"

For Huang Renxun, this is undoubtedly a timely and critical defense battle:

Major client returns: It has been reported that OpenAI has agreed to become one of the first and largest customers for this processor.

Dealing with the "self-research trend": In recent months, OpenAI has been actively seeking alternatives to NVIDIA chips and recently signed a deal with another chip startup.

Major victory: By providing customized and more efficient hardware, NVIDIA successfully brought back its core customers from the edge of "self-researching chips" into its ecosystem.

Industry Insight: The AI competition enters the "efficiency era"

NVIDIA’s recent strategy adjustment sends a clear signal: when model size reaches trillions of parameters, simply stacking compute power is no longer the only solution; inference efficiency will become the lifeline for the commercialization of AGI. By integrating Groq's technology and customizing for OpenAI, NVIDIA is trying to build a second moat in the competitive chip market through "customized services."