Huang Renxun previews "unprecedented" new chip products; the next-generation Feynman architecture may become the focus

NVIDIA CEO Jensen Huang revealed overnight in an interview with Wccftech that the company will unveil a “never-before-seen” new chip product at this year’s GTC conference. This statement has sparked significant market attention regarding NVIDIA’s next-generation product roadmap, with analysts suggesting the new release may involve derivatives of the Rubin series or a more revolutionary Feynman architecture chip.

Huang said:

We have prepared several all-new chips that the world has never seen before. This is no easy feat, as all technologies are approaching physical limits.

Considering NVIDIA recently showcased the Vera Rubin AI series, now entering full production at CES 2026, including six new-designed chips, the market expects this GTC to introduce even more cutting-edge technology solutions. For investors closely watching AI infrastructure competition, this could mean NVIDIA once again setting new industry standards.

NVIDIA’s GTC keynote will be held on March 15 in San Jose, California, where the next phase of AI infrastructure competition will be a core focus.

Two Major Possibilities for the New Product

According to Wccftech, although Huang did not specify detailed product information, the description of “never before seen” points to two main directions.

The first possibility is derivatives of the Rubin series, such as the previously leaked Rubin CPX. NVIDIA recently announced the Vera Rubin AI series at CES 2026, including six chips such as Vera CPU and Rubin GPU, all now in full production.

The second, more disruptive possibility is that NVIDIA may reveal the next-generation Feynman architecture chip ahead of schedule. Industry insiders consider Feynman to be a “revolutionary” product, potentially utilizing more extensive SRAM integration and even stacking LPU (Language Processing Units) through 3D stacking technology, though this technical approach has not been officially confirmed.

Computing Demand Driving Product Evolution

NVIDIA is currently facing a market environment where computing demands are changing quarter by quarter. Huang’s remarks reflect a clear understanding of the technological evolution path.

During the Hopper and Blackwell eras, pre-training was the primary need; but with the launch of Grace Blackwell Ultra and Vera Rubin, inference capabilities have become central, with latency and memory bandwidth now the main bottlenecks. This shift in demand directly influences NVIDIA’s product design direction.

For the Feynman architecture, market expectations are that it will be deeply optimized for inference scenarios. NVIDIA is exploring ways to break through current performance bottlenecks by integrating larger-scale SRAM and possibly incorporating LPU, which could have significant implications for cloud service providers and enterprise customers relying on AI inference.

Additionally, Huang emphasized the importance of broader partnerships and investment strategies. He stated, “NVIDIA has excellent partners and outstanding startups, and we are investing across the entire AI stack. AI is not just a model; it’s a complete industry covering energy, semiconductors, data centers, cloud, and applications built on top of it.” This indicates NVIDIA is shifting from merely a chip supplier to an AI ecosystem builder. Through acquisitions and collaborations, the company aims to maintain its leadership in the AI infrastructure race.

Risk Warning and Disclaimer

Market risks exist; please invest cautiously. This article does not constitute personal investment advice and does not consider individual users’ specific investment goals, financial situations, or needs. Users should evaluate whether any opinions, viewpoints, or conclusions herein are suitable for their particular circumstances. Investment is at your own risk.