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Nvidia will now make new AI chips every year

Nvidia’s recent financial success, driven by the booming demand for its AI chips, has prompted the company to adopt an accelerated development schedule. Nvidia CEO Jensen Huang announced during the company’s Q1 2025 earnings call that Nvidia will now release new chips annually instead of biennially. This shift marks a significant change in their production rhythm, as the company plans to introduce a new chip architecture every year.

Key Points from Nvidia’s Q1 2025 Earnings Call:

  1. Financial Performance: Nvidia achieved $14 billion in profit in a single quarter, primarily fueled by the high demand for AI chips.
  2. Accelerated Development Cycle:
    • Historically, Nvidia introduced new architectures roughly every two years (e.g., Ampere in 2020, Hopper in 2022, Blackwell in 2024).
    • Moving forward, Nvidia will release new architectures annually. The next architecture, reportedly named “Rubin,” is expected in 2025, suggesting an R100 AI GPU release next year.
  3. Comprehensive Chip Advancements:
    • Nvidia plans to accelerate the development of all its chip types, including CPUs, GPUs, networking NICs, and switches.
    • Huang emphasized a fast-paced innovation cycle to ensure Nvidia remains at the forefront of AI and computing technology.
  4. Backward Compatibility:
    • Nvidia’s new AI GPUs are designed to be electrically and mechanically backward-compatible, ensuring seamless integration and transition within existing data center infrastructures.
  5. Market Demand and Strategic Sales Pitches:
    • Huang highlighted the substantial and growing demand for Nvidia’s AI GPUs, with customers eager to upgrade to the latest technology to optimize cost-efficiency and performance.
    • He also used a “fear of missing out” (FOMO) argument to emphasize the competitive advantage of being a leader in AI innovation.
  6. Automotive Sector Growth:
    • Nvidia’s CFO noted that the automotive sector would become the largest enterprise vertical within their data center business this year. Tesla’s purchase of 35,000 H100 GPUs to enhance its “full-self driving” system underscores this growth.
  7. Massive Orders from Major Tech Companies:
    • Companies like Meta are planning to deploy over 350,000 H100 GPUs by the end of the year, highlighting the vast scale of AI infrastructure investments.

Implications of Nvidia’s Strategy:

  1. Innovation Leadership: By accelerating its chip release schedule, Nvidia aims to maintain its leadership in the AI and semiconductor industries, continually offering cutting-edge technology.
  2. Market Adaptation: The backward compatibility feature ensures that existing customers can easily upgrade their systems, fostering customer loyalty and reducing potential disruption during transitions.
  3. Competitive Edge: Nvidia’s emphasis on rapid innovation and substantial investments in AI technology positions it to stay ahead of competitors and meet the evolving needs of industries relying heavily on AI, such as automotive and consumer internet.


Nvidia’s shift to an annual chip development cycle underscores its commitment to rapid innovation and responsiveness to market demand. This strategy not only strengthens Nvidia’s position in the AI and semiconductor markets but also ensures that its customers have access to the latest advancements, driving further growth and technological progress.

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