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ONNX Runtime | Home

Integrate the power of Generative AI and Large language Models (LLMs) in your apps and services with ONNX Runtime. No matter what language you develop in or what platform you need to run on, you can make use of state-of-the-art models for image synthesis, text generation, and more.

import onnxruntime as ort

model_path = "path/to/your/onnx/model"
session = ort.InferenceSession(model_path)

...

outputs = session.run(None, {"input": inputTensor})
print(outputs)

Do you program in Python? C#? C++? Java? JavaScript? Rust? No problem. ONNX Runtime has you covered with support for many languages. And it runs on Linux, Windows, Mac, iOS, Android, and even in web browsers.

CPU, GPU, NPU - no matter what hardware you run on, ONNX Runtime optimizes for latency, throughput, memory utilization, and binary size. In addition to excellent out-of-the-box performance for common usage patterns, additional model optimization techniques and runtime configurations are available to further improve performance for specific use cases and models.

ONNX Runtime powers AI in Microsoft products including Windows, Office, Azure Cognitive Services, and Bing, as well as in thousands of other projects across the world. ONNX Runtime is cross-platform, supporting cloud, edge, web, and mobile experiences.

Run PyTorch and other ML models in the web browser with ONNX Runtime Web.

Infuse your Android and iOS mobile apps with AI using ONNX Runtime Mobile.

ONNX Runtime reduces costs for large model training and enables on-device training.

On-device training with ONNX Runtime lets developers take an inference model and train it locally to deliver a more personalized and privacy-respecting experience for customers.

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