Nvidia RTX Pro 6000 Blackwell Server Edition GPU

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英伟达三大AI重磅产品齐发,GPU服务器性能暴增18倍
3 6 Ke· 2025-08-12 10:49
Core Insights - Nvidia is expanding its AI model offerings, robotic physical intelligence solutions, and enterprise-level AI server product lines [1] - The company unveiled the Nvidia RTX Pro 6000 Blackwell Server Edition GPU, designed for enterprise servers, enabling high-speed operation of large language models [1] - Nvidia's CEO Jensen Huang emphasized that AI is reshaping the computing landscape, transitioning from cloud to local data center architectures [1] Group 1: AI Models and Server Solutions - The new Blackwell RTX Pro servers will enhance traditional CPU-based workloads, achieving performance improvements of up to 45 times and energy efficiency gains of 18 times compared to pure CPU systems [1] - Nvidia is collaborating with major server suppliers like Cisco, Dell, HPE, Lenovo, and Super Micro to offer various configurations of the new servers [2][4] Group 2: Advanced AI Agent Models - Nvidia is expanding its Nemotron model family with two new models, Nemotron Nano 2 and Llama Nemotron Super 1.5, aimed at creating smarter AI agents capable of complex reasoning and planning [5] - The Nemotron Nano 2 boasts a token generation throughput increase of up to 6 times compared to other models in its class, while Llama Nemotron Super 1.5 excels in inference accuracy for complex enterprise tasks [5] Group 3: Physical AI and Reasoning Robots - Nvidia is introducing new AI models that provide robots with perception and reasoning capabilities, integrating visual information processing with cognitive functions [7][9] - The newly launched Cosmos Reason is a customizable 7 billion parameter reasoning VLM designed for physical AI visual agents and robots, enabling them to think about their observations and plan actions based on physical knowledge [9] - Collaborations with companies like Accenture, Belden, and DeepHow aim to enhance productivity and safety in various environments through physical AI-based perception and reasoning [9]