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TensorRT vs ONNX Runtime
Side-by-side comparison of TensorRT (Framework) and ONNX Runtime (Framework).
Live Data← All Comparisons
77.5
Composite Score
TensorRT
Framework · NVIDIA
77.2
Composite Score
ONNX Runtime
Framework · Microsoft
Overall Winner
TensorRT
TensorRT wins 2 of 6 categories · ONNX Runtime wins 2 of 6 categories
Score Comparison
TensorRTvsONNX Runtime
Composite
77.5:77.2
Adoption
80:80
Quality
85:90
Freshness
70:75
Citations
75:70
Engagement
65:65
Details
FieldTensorRTONNX Runtime
TypeFrameworkFramework
ProviderNVIDIAMicrosoft
VersionN/AN/A
Categoryai-frameworksai-frameworks
Pricingfreeopen-source
LicenseProprietaryMIT License
DescriptionNVIDIA TensorRT is an SDK for high-performance deep learning inference. It optimizes trained neural networks for deployment on NVIDIA GPUs, providing significant speedups and reduced latency compared to running models directly in training frameworks.ONNX Runtime is a cross-platform, high performance scoring engine for Open Neural Network Exchange (ONNX) models. It is designed to accelerate machine learning inferencing across a wide range of hardware and operating systems, optimizing model execution for speed and efficiency.
Capabilities
Only TensorRT
graph optimizationlayer fusionkernel auto-tuninglow latency inference
Shared
quantization
Only ONNX Runtime
model-optimizationhardware-accelerationcross-platform-deployment
Integrations
Only TensorRT
None
Shared
None
Only ONNX Runtime
TensorFlowPyTorchscikit-learnCUDADirectML
Tags
Only TensorRT
deep-learninggpunvidia
Shared
inferenceoptimization
Only ONNX Runtime
cross-platformonnx
Use Cases
TensorRT
- ▸real time video analytics
- ▸autonomous vehicles
- ▸recommendation systems
- ▸natural language processing deployment
ONNX Runtime
- ▸image recognition
- ▸natural language processing
- ▸speech recognition
- ▸recommendation systems
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