NVIDIA Pushes Boundaries with Blackwell GPU, Delivering Groundbreaking Performance for AI and LLMs
As generative AI adoption accelerates, NVIDIA's Blackwell and Hopper architecture set new benchmarks in real-time large language model performance, with support from leading industry partners.
NVIDIA platforms lead MLPerf benchmarks, showcasing groundbreaking advances in AI inference performance across data centers and edge AI.
NVIDIA has once again demonstrated its dominance in the AI space with the first submission of its Blackwell GPU, which delivers up to 4x more performance on the Llama 2 70B large language model (LLM) compared to its predecessor, the NVIDIA H100 Tensor Core GPU. This was revealed during the latest MLPerf Inference v4.1 industry benchmarks, where NVIDIA platforms showcased leading performance across all data center tests.
As the demand for generative AI continues to grow, data center infrastructure is under increasing pressure. Training LLMs is just one part of the challenge, with real-time service delivery presenting another significant hurdle. NVIDIA’s new Blackwell platform, leveraging a second-generation Transformer Engine and FP4 Tensor Cores, sets new standards for AI performance. This upgrade is particularly impactful for large-scale LLMs, such as the Llama 2 70B, where performance gains are crucial for efficient real-time services.
NVIDIA’s H200 Tensor Core GPU also delivered exceptional results in the data center category. It excelled in benchmarks for the Mixtral 8x7B mixture of experts (MoE) LLM, known for its efficiency and versatility in handling diverse AI tasks.
The rise of LLMs is driving a significant need for advanced computing capabilities, especially in real-time inference processing. NVIDIA’s Hopper architecture, along with technologies like NVLink and NVSwitch, plays a pivotal role in enabling high-bandwidth communication between GPUs, making large-scale model inference more cost-effective and efficient.
NVIDIA’s relentless software innovation, including platforms like the Triton Inference Server and Jetson, further underscores its commitment to pushing the boundaries of AI performance. The company’s platforms are continuously optimized, with the H200 GPU showing up to 27% more generative AI inference performance in this benchmark round compared to previous iterations.
NVIDIA’s success is shared with its partners, including ASUSTek, Cisco, Dell Technologies, and others, who made strong MLPerf submissions, emphasizing the widespread availability of NVIDIA’s AI platforms across the industry.
With such impressive advancements, NVIDIA continues to lead the charge in the AI revolution, empowering enterprises to meet the growing demands of generative AI and deliver transformative AI-powered services across various industries.
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