Silicon Labs AI/ML SDK Version 3.0.0 - Release Notes (Jun 23, 2026)#

Silicon Labs AI/ML Version 3.0.0

Simplicity SDK Version 2026.6.0

The Silicon Labs AI/ML SDK is provided as an extension to the Simplicity SDK. It enables AI/ML development on Series 2 (EFR and SiWG917) devices using the Tensorflow Lite for Microcontrollers (TFLM) framework.

Release Summary#

Key Features | API Changes | Bug Fixes | Chip Enablement

Key Features#

  • Breaking Change: New DX for adding ML Models to new or existing projects.

  • Breaking Change: New APIs to initialize, execute, and de-initialize ML models.

  • Project upgrades require manual effort. See the AI-assisted migration prompt.

  • New optimization features to enable faster inference with .tflite models.

  • Model code generation now triggers on .mlconf files instead of .tflite files.

  • Multiple-Model feature to add and execute multiple ML models in a project.

  • Added SiWG917 Multiple-Model sample applications: Voice control + blink (experimental).

  • Compiler compatibility upgraded: GCC 14.2 Rel1 (all platforms) and IAR 9.70.3 (EFR32 only).

  • Replaced "Tensorflow Lite Micro" with "ML Model" as the starter component.

  • Added Voice Controlled Light over Wi-Fi sample application.

  • Unified ML sample and demo application naming in Simplicity Studio.

  • CMSIS-DSP upgraded to v1.16.2 from v1.15.0.

API Changes#

  • New: sl_ml_model_init(), sl_ml_model_run(), and sl_ml_model_deinit() APIs support adding Multiple Models.

  • Deprecated: Legacy model-specific APIs (sl_ml_<model>_model_init() / _run(), slx_ml_* variants, and per-model globals).

  • Deprecated: TFLite Micro init, tensor, arena, and interpreter APIs for application use (still present in SDK).

  • Changed: Use ml_model as the starter component instead of adding tensorflow_lite_micro directly. The ml_model component requires tensorflow_lite_micro and brings in the generic model APIs.

Bug Fixes#

  • Fixed microphone integration on SiWG917 (BRD2605A) using ULP_I2S interface.

Chip Enablement#

  • Added support for EFM32 devices.

Key Features#

New Features | Enhancements | Removed Features | Deprecated Features

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

New Features#

  • New developer experience for ML models: The ml_model component is the new starter component for adding ML models to new or existing projects. It requires tensorflow_lite_micro and brings in the generic model APIs. Model code generation triggers on .mlconf files instead of .tflite files. Existing projects cannot be upgraded automatically and require manual migration. See the AI/ML 3.0 Migration Guide.

  • Model runtime APIs: New sl_ml_model_init(), sl_ml_model_run(), and sl_ml_model_deinit() APIs replace the TFLite Micro Interpreter based execution flow and legacy per-model init/run APIs. These APIs use instance-based model handles (sl_ml_<model>_model_handle) and support adding Multiple Models to a project.

  • Multiple-Model support: Sample applications demonstrate Multiple-Model execution on EFR32 and SiWG917, including Voice control + blink on SiWG917.

  • Model optimization: Software optimizations enable faster inference with .tflite models on SiWG917. Series 2 devices do not receive these new optimizations but remain at least as efficient due to their architecture.

  • Voice Controlled Light over Wi-Fi: Added a new sample application combining on-device voice control with Wi-Fi connectivity on SiWG917.

  • EFM32 device support: Added support for EFM32 devices.

Enhancements#

  • Compiler support: All AIML applications now build with GCC 14.2. IAR 9.70.3 is supported on EFR32 devices only. CMSIS-DSP and CMSIS-NN libraries are rebuilt with both GCC 14.2 and IAR 9.70.3.

  • CMSIS-DSP upgrade: AI/ML now depends on CMSIS-DSP v1.16.2 (previously v1.15.0).

  • Starter component: "ML Model" replaces "Tensorflow Lite Micro" as the starter component in Simplicity Studio for adding ML models to projects.

  • Component dependency: The ml_model component requires the tensorflow_lite_micro component. The tensorflow_lite_micro component is not removed; it continues to provide the underlying TFLM runtime and is pulled in automatically when ml_model is used.

  • Application naming: Unified ML sample and demo application names in Simplicity Studio. Project names follow the aiml_<soc|wireless_tech>_<app-name>[_<micriumos|freertos>] convention and display as AI/ML - SoC [Wireless Technology] <App Name> [<MicriumOS | FreeRTOS>] <EFR32 | SiWG917>.

Removed Features#

Removed Feature

Was Deprecated?

TFLite Micro Interpreter based application execution flow

No

Per-model autogenerated init/run API pattern (sl_ml_<model>_model_init() / _run())

No

Using tensorflow_lite_micro directly as the project starter component

No

Applications must migrate to the generic sl_ml_model_init(), sl_ml_model_run(), and sl_ml_model_deinit() APIs with instance-based handles. See the AI/ML 3.0 Migration Guide.

Deprecated Features#

None.

API Changes#

New APIs | Modified APIs | Removed APIs | Deprecated APIs

New APIs#

New API Signature

Deprecated API replaced by this (if any)

sl_ml_model_init(sl_ml_<model>_model_handle&)

sl_ml_<model>_model_init(), sl_tflite_micro_init()

sl_ml_model_run(sl_ml_<model>_model_handle&)

sl_ml_<model>_model_run(), TFLite Micro Interpreter based execution

sl_ml_model_deinit(sl_ml_<model>_model_handle&)

None.

sl_ml_<model>_model_handle (autogenerated)

<model>_model, per-model globals in sl_ml_model_<model>.h

sl_ml_<model>_model_handle.model

<model>_model

Return value of sl_ml_model_init() / sl_ml_model_run()

<model>_model_status

sl_ml_<model>_model_handle.flatbuffer

<model>_model_flatbuffer

sl_ml_<model>_model_handle.flatbuffer_length

<model>_model_flatbuffer_length

sl_ml_<model>_model_handle.input_tensor(0)

sl_tflite_micro_get_input_tensor()

sl_ml_<model>_model_handle.output_tensor(0)

sl_tflite_micro_get_output_tensor()

Modified APIs#

None.

Removed APIs#

The following APIs and patterns are no longer generated or supported in application code. Use the replacements in Deprecated APIs.

Removed API Name

Was Deprecated?

sl_ml_<model>_model_init()

No

sl_ml_<model>_model_run()

No

slx_ml_<model>_model_init() / _run()

No

sl_ml_<model>_model_init()

No

sl_ml_<model>_model_run()

No

slx_ml_<model>_model_init() / _run()

No

<model>_model

No

<model>_model_status

No

<model>_model_flatbuffer

No

<model>_model_flatbuffer_length

No

sl_tflite_micro_init()

No

sl_tflite_micro_get_input_tensor()

No

sl_tflite_micro_get_output_tensor()

No

sl_tflite_micro_get_interpreter()

No

sl_tflite_micro_get_error_reporter()

No

sl_tflite_micro_estimate_arena_size()

No

sl_tflite_micro_allocate_tensor_arena()

No

sl_tflite_micro_opcode_resolver()

No

sl_tflite_micro_enable_debug_log()

No

sl_tflite_micro_is_debug_log_enabled()

No

Deprecated APIs#

None.

Bug Fixes#

ID Issue Description GitHub / Salesforce Reference Affected Software Variants, Hardware, Modes, Host Interfaces
— Fixed an issue where microphone integration on SiWG917 (BRD2605A) using the ULP_I2S interface was not functioning as expected. None
  • SiWG917 (BRD2605A)
  • SoC

Chip Enablements#

Chip Family OPNs / Boards / OPN Combinations Supported Software Variants (if applicable) Supported Modes Supported Host Interfaces
EFM32
  • EFM32 devices (new in this release)
 Standard SoC
  • UART
  • SPI
  • I2C

Application Example Changes#

New Examples | Modified Examples | Removed Examples | Deprecated Examples

New Examples#

Example Name

Description

AI/ML - SoC Voice Control Light + Sine Blink concurrent MicriumOS EFR32

EFR32 Multiple-Model example running voice control and blink models concurrently.

AI/ML - SoC Voice Control Light + Sine Blink sequential MicriumOS EFR32

EFR32 Multiple-Model example running voice control and blink models sequentially.

AI/ML - SoC Voice Control Light + Sine Blink concurrent SiWG917

SiWG917 Multiple-Model example running voice control and blink models concurrently.

AI/ML - SoC Voice Control Light + Sine Blink sequential SiWG917

SiWG917 Multiple-Model example running voice control and blink models sequentially.

Voice Controlled Light over Wi-Fi

Sample application combining on-device voice control with Wi-Fi connectivity on SiWG917.

Modified Examples#

Example Name

Changes

All AIML sample and demo applications

Unified naming convention in Simplicity Studio. Project names follow aiml_<soc|wireless_tech>_<app-name>[_<micriumos|freertos>] and display as AI/ML - SoC [Wireless Technology] <App Name> [<MicriumOS | FreeRTOS>] <EFR32 | SiWG917>.

Removed Examples#

None.

Deprecated Examples#

None.

Known Issues and Limitations#

  • Series 2 devices do not support new software optimizations for inference. However, due to their architecture, they are still at least as efficient as SiWG917.

  • IAR 9.70.3 is not supported on SiWG917 devices.