Compile ML models into dependency-free source code for easy deployment
I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a compiler that simply converts the model into plain source code with no dependencies, and it actually solved all my deployment problems. Now I'm curious if it can help anyone else too. Through the link you can submit your model file (Keras h5, onnx soon to be supported), and I'll…
Compile ML models into dependency-free source code for easy deployment launched on April 5, 2023 with 37 votes, #1,485 of 4,853 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
This tool converts machine learning models into standalone source code without external dependencies, making it easier to deploy models on mobile apps, smartwatches, and microcontroller firmware. Users can submit Keras or ONNX model files, and the compiler generates pure code that eliminates library overhead and compatibility issues. It's designed for developers and ML engineers who need lightweight model deployment without runtime dependencies.
written from the facts on this page · September 2026
From the sources
Flow Coder takes the pain out of integrating a machine learning model into your software or firmware project. It converts trained machine learning models straight into dependency-free source code for many common programming languages, thereby eliminating the complexity and overhead of inference libraries in deployment projects. The compiler can be invoked online, using a desktop tool or as a single executable command-line tool, so it’s easy to integrate as a pre-build step in a build pipeline. The compiler supports all layers and operations including quantizedfrom waveworks.dk
In the maker’s words, at launch
I'm a machine learning engineer who always found it annoying to integrate ML models into phone apps, smartwatch apps, microcontroller firmware etc... Why do we need all these libraries and runtimes with all the overhead, compatibility issues and other headaches, when it's just some math to be executed? So I made a…
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