CUDA-X
…NVIDIA Video Codec SDK Hardware-accelerated video encode and decode on Windows and Linux. NVIDIA Optical Flow SDK Exposes the latest hardware capability of NVIDIA GPUs dedicated to computing the relative motion…
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What metrics should you measure for LLM inference performance?
The prerequisite for sizing and TCO estimation is benchmarking the performance of each deployment unit, e.g., an inference server. The goal of this step is to measure the throughput a system can produce under load, and at what latency. These throughput and latency metrics, together with quality of service requirements (e.g., max latency) and expected peak demand (e.g., max concurrent users or requests per second), will help estimate the required hardware, such as sizing the deployment. In turn, sizing information is a prerequisite for estimating the total cost of ownership (TCO) of the given s
LLM Inference Benchmarking: How Much Does Your LLM Inference Cost? | NVIDIA Technical BlogNVIDIA Streamline SDK 2.4
…Should I enable Streamline on non-NVIDIA hardware? A: Yes. Streamline is an open-source SDK developed by NVIDIA, it supports multiple features that work across all hardware vendors. These features include…
Building Token‑Metered AI Services on Telco AI Factories | NVIDIA Technical Blog
…Token-as-a-Service transforms raw GPU infrastructure into AI applications and APIs measured by tokens, supported by AI developer studios for model fine-tuning and AI marketplaces for service deployment. AI…
Inside the NVIDIA Vera Rubin Platform: Six New Chips, One AI Supercomputer | NVIDIA Technical Blog
…Validate hardware and cluster performance throughout the life cycle of your infrastructure. Enterprise software and lifecycle support NVIDIA AI Enterprise provides the enterprise-grade software foundation required to operate AI factories at…
Jetson FAQ
…It will support Jetson Orin series 2026 JetPack 6 is in sustaining mode. It supports Jetson Orin with production-ready feature releases. It also supports Jetson Platform Services, Upgradable AI compute stack…
Introducing NVIDIA BlueField-4-Powered CMX Context Memory Storage Platform for the Next Frontier of AI | NVIDIA Technical Blog
…The NVIDIA DOCA framework, Spectrum-X Ethernet, and orchestration tools like NVIDIA Dynamo and NIXL coordinate context placement, KV block management, and workload scheduling across the memory hierarchy, supporting efficient, stateless sharing…
Accelerating AI-Powered Chemistry and Materials Science Simulations with NVIDIA ALCHEMI Toolkit-Ops | NVIDIA Technical Blog
…Capabilities Both O(N) (cell list) and O(N²) (naive) algorithms with batched processing Periodic boundary support for triclinic cells with arbitrary cell dimensions and partial periodicity Supports end-to-end compute…
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