…while giving insight into the CPU and GPU behavior of CUDA applications. Normally packaged with the CUDA Toolkit, NVIDIA occasionally uses this page to provide CUPTI improvements and bug fixes between toolkit…
…LoRA SFT on Nemotron 3 Nano Omni using NVIDIA NeMo Megatron-Bridge . LoRA SFT on Nemotron 3 Nano Omni using NVIDIA NeMo Automodel . GRPO/MPO on Nemotron 3 Nano Omni using NeMo…
…TensorRT for RTX is only compatible with NVIDIA RTX GPUs, from the Turing generation (compute capability 7.5) up to the NVIDIA Blackwell generation (compute capability 10.0). Unreal Engine neural network…
…of multiple images using a single decoder, reducing per-image decode times by up to ~85% for large batches on NVIDIA GPUs. Profiling with NVIDIA Nsight Systems and NVIDIA Nsight Compute identified…
…on NVIDIA Blackwell, as demonstrated in the recent SemiAnalysis InferenceX benchmark. SemiAnalysis InferenceX, updated March 3, 2026. Results for DeepSeek R1-0528, FP4, 1k/1k, interactivity: ~50 tok/sec/user. This blog…
…Triton users will be able to select which backend (PTX backend or CUDA Tile IR backend) to use on a per-kernel basis in their applications. Development road map of Triton-to…
…Using CPU TEEs paired with NVIDIA confidential GPUs (like NVIDIA Hopper or NVIDIA Blackwell) for hardware-accelerated, memory-encrypted AI workloads. Kata Containers runtime : Wrapping standard Kubernetes Pods in lightweight, hardware-isolated…
…Getting Started To build in-vehicle AI applications on AI Box built on the NVIDIA DRIVE AGX platform: Prototype in the cloud using NeMo and NIMs Leverage TensorRT-LLM for optimized inference…
…The 35B parameter VLM is suited for data center GPUs such as NVIDIA Grace Blackwell and NVIDIA Vera Rubin, and consumer cards like NVIDIA DGX Spark. With the NVIDIA NeMo Agent Toolkit…
…The challenge of numerical disagreement in RL RL pipelines typically use separate engines: vLLM for rollouts and NVIDIA Megatron Core for training. Each uses unique custom NVIDIA CUDA kernels to maximize performance…