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GB300 NVL72 offers 13x better performance per dollar than Hopper for agentic inference

By PulseAugur Editorial · [1 sources] ·

SemiAnalysis reports that the GB300 NVL72, utilizing an innovative copper backplane and NVLink, offers a 13x improvement in performance per dollar compared to NVIDIA's Hopper architecture for agentic inference. This advanced design enables a scale-up domain of 72 GPUs, significantly larger than Hopper's 8, facilitating optimizations like vLLM's wide expert parallelism. AI

IMPACT This hardware advancement could significantly reduce the cost of running large AI models, particularly for agentic inference tasks.

RANK_REASON The item discusses a new hardware architecture and its performance benefits, which falls under research into hardware capabilities. [lever_c_demoted from research: ic=1 ai=0.7]

Read on X — SemiAnalysis →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GB300 NVL72 offers 13x better performance per dollar than Hopper for agentic inference

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The item discusses a new hardware architecture and its performance benefits, which falls under research into hardware capabilities. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. X — SemiAnalysis TIER_1 Deutsch(DE) · SemiAnalysis_ ·

    ALERT🚨 GB300 NVL72 NVLINK BACKPLANE ENABLES 13x BETTER PERF PER DOLLAR THAN HOPPER ON AGENTIC INFERENCE

    ALERT🚨 GB300 NVL72 NVLINK BACKPLANE ENABLES 13x BETTER PERF PER DOLLAR THAN HOPPER ON AGENTIC INFERENCE Through extreme co-design, GB300 NVL72 uses an innovative copper backplane to expand the scale-up domain to 72 versus 8 on Hopper. This allows optimizations like https://t.co/…

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