𝗥eturn On Investment driven by performance Performance per watt per $ = profit. Moving from Hopper to Blackwell delivers 4× more perf and up to 10× profit within the same power budget.
AI HARDWARE
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NVIDIA Blackwell GB200 NVL72 Delivers 50× AI Productivity Gains
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𝗔rchitecture and software The NVIDIA Blackwell platform + GB200 NVL72 rack system = up to 50× higher AI factory productivity. Throughput + energy and water efficiency gains + full-stack orchestration = scalable inference.
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Enterprise AI Infrastructure: Scaling Models and Inference Demands
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𝗦cale and complexity Bigger models = greater inference. From quick queries to million-token reasoning, infra demands during inference are soaring. Enterprises are building new AI factories with partners like @CoreWeave
, @Dell
, @googlecloud and more. -
NVIDIA Inference Platform: Balancing Accuracy, Latency, and Cost
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𝗠ulti-dimensional performance Optimal Inference is a trade-off: accuracy, latency, and cost. Some tasks need ultra-low latency (real-time translation), while others prioritize throughput (multi-million-token queries). The NVIDIA Inference Platform accelerates models
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Smart Inference Deployment: Scaling AI Across Enterprise Systems
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Deploying AI at scale requires you to 𝗧𝗵𝗶𝗻𝗸 𝗦𝗠𝗔𝗥𝗧 about inference: 𝗦cale and complexity 𝗠ulti-dimensional performance
𝗔rchitecture & software
𝗥OI driven by performance
𝗧echnology ecosystem & install base Let’s break it down -
NVIDIA Blackwell GB200 NVL72 50x AI Inference Productivity
By
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𝗔rchitecture and software The NVIDIA Blackwell platform + GB200 NVL72 rack system = up to 50× higher AI factory productivity. Throughput + energy and water efficiency gains + full-stack orchestration = scalable inference.
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Blackwell delivers 4x performance within same power budget
By
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𝗥eturn On Investment driven by performance Performance per watt per $ = profit. Moving from Hopper to Blackwell delivers 4× more perf and up to 10× profit within the same power budget.
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NVIDIA Inference Platform Balances Accuracy Latency Cost Trade-offs
By
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𝗠ulti-dimensional performance Optimal Inference is a trade-off: accuracy, latency, and cost. Some tasks need ultra-low latency (real-time translation), while others prioritize throughput (multi-million-token queries). The NVIDIA Inference Platform accelerates models
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Enterprise AI Infrastructure Scaling for Large Model Inference
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𝗦cale and complexity Bigger models = greater inference. From quick queries to million-token reasoning, infra demands during inference are soaring. Enterprises are building new AI factories with partners like @CoreWeave
, @Dell
, @googlecloud and more. -
DeepSeek v3.1 Uses UE8M0 FP8 Logarithmic Training Format
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It is interesting that the new @deepseek_ai v3.1 is trained using the UE8M0 FP8 scale data format which is logarithmic number system. Our multiplicative weights update (Madam) for training in that format was done several years ago while at @nvidia It yields maximum hardware