Deploy an Open Model from Checkpoint to Inference in Two Commands with NVIDIA TensorRT Model Connect | NVIDIA Technical Blog

This post introduces NVIDIA TensorRT Model Connect, a new reference implementation project that bridges open models from Hugging Face checkpoints to native C++ inference using TensorRT. It details a two-phase deployment workflow: building a bundle from a model ID via a Python CLI, and then loading and running that bundle in a C++ application. It highlights two API levels (semantic and module-level) for flexibility and the integration of custom GPU kernels via TVM FFI. The project emphasizes AI-native development with coding agents and nightly releases to accelerate support for the rapidly evolving open model ecosystem, aiming to deliver faster inference than torch.compile and a consistent deployment path for supported open models.