• As AI workloads scale, achieving high throughput, efficient resource usage, and predictable latency becomes essential. • NVIDIA Run:ai addresses these challenges through intelligent scheduling and dynamic GPU fractioning. • GPU fractioning is wholly delivered by NVIDIA Run:ai in any environment-cloud, NCP, and on-premises. • This post presents the joint benchmarking effort between NVIDIA and AI cloud provider Nebius to evaluate how NVIDIA Run:ai fractional GPU allocation can improve large language model (LLM) inference performance. • Nebius’ AI Cloud provided the infrastructure foundation, dedicated NVIDIA GPUs, NVIDIA Quantum InfiniBand networking, and hyperscaler-grade performance and elasticity needed to deliver these gains at production scale. • All benchmarks were executed using NVIDIA NIM microservices.

Article Summaries:

  • As AI workloads scale, achieving high throughput, efficient resource usage, and predictable latency becomes essential. NVIDIA Run:ai addresses these challenges through intelligent scheduling and dynamic GPU fractioning. GPU fractioning is wholly delivered by NVIDIA Run:ai in any environment-cloud, NCP, and on-premises. This post presents the joint benchmarking effort between NVIDIA and AI cloud provider Nebius to evaluate how NVIDIA Run:ai fractional GPU allocation can improve large language model (LLM) inference performance. Nebius’ AI Cloud provided the infrastructure foundation, dedicated N

Sources: