NVIDIA Lays Out Two-Year AI Roadmap With Beast Rubin GPU, Vera CPU And NVL576

NVIDIA Lays Out Two-Year AI Roadmap With Beast Rubin GPU, Vera CPU And NVL576

  • 18.03.2025 17:45
  • hothardware.com
  • Keywords: AI, GPU

NVIDIA announced its AI roadmap with Vera Rubin and NVL576 GPUs, offering significant performance improvements over previous models. The company clarified its GPU die-counting method, with Vera Rubin delivering 3.3x better performance than Blackwell Ultra. The NVL576 variant, set for release in late 2027, promises 100 petaFLOPS compute and 1TB memory per package, with pricing targeting enterprise-level budgets.

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Analyst rating: Strong buy

NVIDIA is introducing new AI GPUs which could disrupt the market.

Context

NVIDIA Two-Year AI Roadmap Analysis

Key Product Launches

  • Vera Rubin NVL144:

    • Expected release: Second half of 2025.
    • Features: 384 CUDA cores, 100 petaFLOPS FP4 compute, and 1TB HBM4e memory.

  • Rubin Ultra NVL576:

    • Expected release: Second half of 2027.
    • Features: 2.5 million parts, 14 times the performance of Blackwell Ultra GB300 NVL72, and 144 TB HBM4e memory.

Performance Metrics

  • Blackwell vs. Rubin:

    • Rubin offers a 3.3x performance upgrade over Blackwell Ultra.

  • Power Consumption:

    • Rubin Ultra NVL576 draws 600 kilowatts of power.

Pricing and Availability

  • Pricing Strategy:

    • "If you have to ask, you can't afford it" – indicating premium pricing for high-end AI hardware.

  • Availability Timeline:

    • Vera Rubin NVL144: End of 2025.
    • Rubin Ultra NVL576: End of 2027.

Strategic Considerations

  • Focus on High-Performance Computing (HPC):

    • NVIDIA is doubling down on extreme-scale AI with its next-gen GPUs, targeting hyperscalers and research institutions.

  • Energy Efficiency:

    • Despite high power consumption, the focus on performance per watt suggests a balance between raw power and efficiency for demanding workloads.

Market Implications

  • Dominance in AI Hardware:

    • NVIDIA's continued innovation reinforces its leadership in the AI and HPC markets.

  • Competitive Landscape:

    • The release of Vera Rubin and Rubin Ultra positions NVIDIA to further outpace competitors like AMD and Intel in terms of raw compute power.

Long-Term Effects

  • Shift Toward More Scalable Architectures:

    • The move to count GPU dice rather than individual chips reflects a trend toward more modular, scalable designs for AI workloads.

  • Potential Regulatory Impact:

    • High power consumption may prompt scrutiny from regulators focused on energy efficiency and sustainability in data centers.

Competitive Dynamics

  • Race for HPC Leadership:

    • NVIDIA's roadmap underscores the importance of HPC in driving future AI advancements, with competitors likely to respond with similar high-performance offerings.

  • Strategic Partnerships:

    • The focus on extreme-scale computing may drive partnerships with cloud providers and research institutions to maximize hardware utilization.

Conclusion

NVIDIA's two-year AI roadmap signals a bold move to maintain dominance in the HPC and AI markets. The introduction of Vera Rubin and Rubin Ultra, with their unprecedented performance metrics, positions NVIDIA as the leader in extreme-scale AI computing. However, the high power consumption and premium pricing may pose challenges in terms of energy sustainability and accessibility for broader adoption.