NVIDIA TensorRT for RTX is now available for download as an SDK that can be integrated into C++ and Python applications for both Windows and Linux. At Microsoft Build, we unveiled this streamlined solution for high-performance AI inference that supports NVIDIA GeForce RTX GPUs from NVIDIA Turing through NVIDIA Blackwell generations, including the latest NVIDIA RTX PRO lineup.
]]>AI experiences are rapidly expanding on Windows in creativity, gaming, and productivity apps. There are various frameworks available to accelerate AI inference in these apps locally on a desktop, laptop, or workstation. Developers need to navigate a broad ecosystem. They must choose between hardware-specific libraries for maximum performance, or cross-vendor frameworks like DirectML…
]]>The launch of the NVIDIA Blackwell platform ushered in a new era of improvements in generative AI technology. At its forefront is the newly launched GeForce RTX 50 series GPUs for PCs and workstations that boast fifth-generation Tensor Cores with 4-bit floating point compute (FP4)—a must-have for accelerating advanced generative AI models like FLUX from Black Forest Labs. As the latest image…
]]>NVIDIA TensorRT, an established inference library for data centers, has rapidly emerged as a desirable inference backend for NVIDIA GeForce RTX and NVIDIA RTX GPUs. Now, deploying TensorRT into apps has gotten even easier with prebuilt TensorRT engines. The newly released TensorRT 10.0 with weight-stripped engines offers a unique solution for minimizing the engine shipment size by reducing…
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