ONNX Runtime Web
Run ONNX models directly in web browsers with this JavaScript library.
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is ONNX Runtime Web?
ONNX Runtime Web is a JavaScript library that enables running ONNX models on the browser, facilitating machine learning inference without server-side dependencies. It's ideal for developers looking to deploy AI models directly within web applications.
Key differentiator
“ONNX Runtime Web stands out as the only JavaScript library enabling direct ONNX model execution in web browsers, offering unparalleled flexibility and performance for client-side machine learning applications.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Developers building web applications with machine learning capabilities who need to perform model inference on the client side.
Teams working on interactive AI applications that require fast response times and minimal latency.
Projects aiming for offline or low-bandwidth scenarios where server-side dependencies are not feasible.
✕ Not a fit for
Applications requiring real-time streaming of large datasets, as it is optimized for model inference rather than data processing.
Scenarios with strict security requirements that cannot be met by client-side execution of models.
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Next step
Get Started with ONNX Runtime Web
Step-by-step setup guide with code examples and common gotchas.