Simplicity Machine Learning Version 1.1.0-beta Release Notes (Jun 23, 2026)#

The Artificial Intelligence and Machine Learning (AI/ML) tools include Simplicity Machine Learning (formerly ML Profiler), the model graph viewer, and the model converter. Use these tools to prepare and profile models on the host system.

Release Summary#

Key Features | Bug Fixes | Chip Enablement

Key Features#

• The "ML Profiler" tool was renamed to "Simplicity Machine Learning".

• Added an option to choose kernels when profiling a model.

• Improved central processing unit (CPU) and accelerator cycle counts in the profiler.

• Added a model graph viewer to Simplicity Machine Learning based on Model Explorer.

• Added an alpha release of the ML Model Converter to convert PyTorch and Open Neural Network Exchange (ONNX) models to TensorFlow Lite (TFLite).

Bug Fixes#

None.

Chip Enablement#

None.

Key Features#

New Features | Enhancements | Removed Features | Deprecated Features

Note: See Feature Matrix for a list of any applicable application programming interfaces (APIs), examples, software variants, modes, hardware, and host interfaces for each feature.

New Features#

• Simplicity Machine Learning profiler: Renamed from "ML Profiler" to "Simplicity Machine Learning". This host-side tool profiles ML models on target hardware.

• Kernel selection: Added an option to choose kernels when profiling a model.

• Model graph viewer: Integrated a model graph viewer in Simplicity Machine Learning based on Model Explorer. Linux and macOS are supported natively; Windows is supported through Windows Subsystem for Linux (WSL).

• ML Model Converter: Added a unified graphical user interface (GUI) and command-line interface (CLI) to convert PyTorch and ONNX models to TFLite.

• manifest.json output: When --save-manifest command line argument is passed on the CLI, a manifest.json file is saved with conversion metadata including conversion time, conversion ratio, input shape, and output shape. The GUI generates this file every time.

Enhancements#

• Profiler metrics: Improved CPU and accelerator cycle count reporting in Simplicity Machine Learning.

Removed Features#

None.

Deprecated Features#

The "ML Profiler" tool will not receive any updates. In Simplicity Studio, search for Simplicity Machine Learning (GUI) or Simplicity Machine Learning (CLI).

Bug Fixes#

None.

Chip Enablement#

None.

Known Issues and Limitations#

Refer to the ML Profiler Troubleshooting section for known issues and their solutions.

Refer to the ML Model Converter Troubleshooting section for known issues and their solutions.

• The model graph viewer is not supported natively on Windows; use WSL to launch the GUI tool.

• The model converter is not supported natively on Windows; use WSL to launch the GUI tool.

  • ONNX models are converted using onnx2tf. Non-self-contained ONNX models with external weights are rejected with a clear message

  • PyTorch models with dynamic graphs require an explicit input shape input.

  • Quantization is not applied.

  • Output models are generated in float32.

Installation and Use#

Refer to the Getting Started guide for installation and usage instructions.

For information about Secure Vault Integration, see Secure Vault.

Help and Feedback#

• Contact Silicon Labs Support.

• To use the Ask AI tool, see the search field at the top of this page.

• Get help from our developer community.

Feature Matrix#

Supported Features | Unsupported Features

Supported Features#

Unsupported Features#

• The model graph viewer is not supported natively on Windows. Use WSL to launch the GUI tool.

• The model converter is not supported natively on Windows. Use WSL to launch the GUI tool.

SDK Release and Maintenance Policy#

See our SDK Release and Maintenance Policy.