{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/3"},{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/3"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/2"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/5"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics"}],"enrichment":{"capability":"Executes ONNX machine learning models on GPU hardware, providing inference acceleration for neural networks and other machine learning workloads.","skillfed_tags":["gpu-accelerated","inference-engine","neural-networks"],"use_cases":["Accelerate inference for computer vision models (object detection, image classification) in production systems.","Run real-time NLP model inference (transformers, language models) with GPU speedup for low-latency predictions.","Deploy quantized or optimized ONNX models on GPU for high-throughput batch inference in data pipelines.","Execute recommendation system models on GPU for fast scoring in online serving environments.","Benchmark or evaluate model performance on GPU hardware during model development and optimization."],"what_it_does":"ONNX Runtime GPU is a performance-focused inference engine that executes Open Neural Network Exchange (ONNX) models on NVIDIA GPUs. It takes pre-trained models in ONNX format and runs them efficiently on GPU hardware, accelerating predictions for machine learning workloads. The package depends on flatbuffers, numpy, packaging, and protobuf for model serialization, numerical operations, and dependency management.\n\nThis is the GPU-specific variant of ONNX Runtime, designed for scenarios where inference speed matters and GPU hardware is available. It's commonly used in production systems, real-time inference pipelines, and research environments where model throughput or latency is critical. The package is maintained by Microsoft, actively developed, and supports recent Python versions (3.11\u20133.14) across Linux and Windows platforms.","worth_installing":"Yes, if you have GPU hardware available and need to run ONNX models in production or research. The package is actively maintained, permissively licensed, and widely used (top 5000 PyPI). Install friction is moderate due to GPU driver/CUDA setup requirements, but the package itself is stable and well-supported. Not suitable if you lack GPU hardware or need CPU-only inference."},"id":"onnxruntime-gpu","links":{"html":"https://skillfed.io/packages/onnxruntime-gpu","md":"https://skillfed.io/packages/onnxruntime-gpu.md","pypi":"https://pypi.org/project/onnxruntime-gpu/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-25","license_spdx":null,"license_treatment":"permissive","name":"onnxruntime-gpu","python_support":"supports_current","summary":"ONNX Runtime is a runtime accelerator for Machine Learning models"},"popularity":{"monthly_downloads":3493668,"position":2600,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.28.0"}