{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"Provides Python bindings for NVIDIA TensorRT 11, enabling high-performance deep learning inference on CUDA 12 GPUs through optimized model compilation and execution.","skillfed_tags":["gpu-inference","model-optimization","cuda"],"use_cases":["Compile trained models (ONNX, PyTorch) into optimized TensorRT engines for low-latency serving on NVIDIA GPUs.","Deploy LLMs, vision models, and encoder-NLP architectures with explicit quantization and graph optimization for production inference.","Benchmark and profile inference performance across different batch sizes and precision modes.","Integrate custom layers via IPluginV3 to extend TensorRT's operator coverage for specialized model architectures."],"what_it_does":"tensorrt-cu12 is the Python interface to NVIDIA's TensorRT 11.2.1.2 inference engine, optimized for CUDA 12 GPUs. It compiles and executes deep learning models with minimal latency and memory overhead, supporting import paths from ONNX, PyTorch, and HuggingFace. Version 11 introduced breaking changes: weakly-typed networks and implicit quantization have been removed in favor of strongly-typed networks and explicit quantization; IPluginV2 has been replaced by IPluginV3; and Python 3.9 and older are no longer supported.\n\nThe package depends on tensorrt_cu12_libs and tensorrt_cu12_bindings, which provide compiled libraries and low-level bindings. Installation requires pre-existing CUDA and TensorRT GA build infrastructure. It is intended for developers deploying inference workloads on NVIDIA GPUs where model throughput and latency are critical, not for training or development on CPU-only systems.","worth_installing":"Yes, if you have CUDA GPU infrastructure and need production-grade inference acceleration. High install friction and proprietary licensing require upfront commitment to NVIDIA's ecosystem. Active maintenance and no known vulnerabilities are positive signals. Not suitable for development without dedicated GPU hardware or for environments where proprietary licensing is prohibited."},"id":"tensorrt-cu12","links":{"html":"https://skillfed.io/packages/tensorrt-cu12","md":"https://skillfed.io/packages/tensorrt-cu12.md","pypi":"https://pypi.org/project/tensorrt-cu12/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-30","license_spdx":null,"license_treatment":"unclear","name":"tensorrt-cu12","python_support":"supports_current","summary":"A high performance deep learning inference library"},"popularity":{"monthly_downloads":226275,"position":9202,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"11.2.1.2"}