Implementing AI/ML on KW45B41Z-EVK

Srushti_Mulimani — Fri, 04 Sep 2026 12:32:20 GMT

Hi NXP Community,

I am working on an edge AI application for the KW45B41Z-EVK (Cortex-M33) and would like advice on deploying a machine learning model on this board.

Since the KW45 SDK does not include the eIQ/TFLM middleware by default, my plan is:

Model Training: Train an n-class classification model for time-series data using eIQ Time Series Studio (eIQ TSS). Since the KW45 is not listed as a target in eIQ TSS, I selected the FRDM-MCXN947 (Cortex-M33) as the target platform to export the model.
Runtime Deployment: Port the middleware/eiq/tensorflow-lite folder from the FRDM-MCXN947 SDK into my KW45 SDK project and link it with CMSIS-NN.

My Questions:

Is porting the eIQ TFLM middleware from the MCXN947 SDK to the KW45 SDK a valid and supported approach?
Is selecting the FRDM-MCXN947 in eIQ TSS suitable for generating models to run on the KW45?
Is there any other recommended or native workflow to implement AI/ML on the KW45B41Z-EVK?

Thanks for your help!
#AIML

Re: Implementing AI/ML on KW45B41Z-EVK

sofiaurueta — Tue, 08 Sep 2026 17:41:14 GMT

Hello, hope you are doing well.

If you are using eIQ Time Series Studio (TSS), I would recommend porting your project from the FRDM-MCXW71 instead. It is an officially supported target in eIQ TSS and is software compatible with the KW45. Both devices share the same Cortex-M33 core architecture and a similar memory profile, so the generated library should be a much closer match for your hardware.

When using a device with such a different hardware profile as the FRDM-MCXN947 as a target for porting, there is a risk of generating incompatible models, for example, due to the differences in available RAM between both devices, or the generation of NPU-accelerated models specific to the MCXN947.

Hope this helps!

Best regards,
Sofia.

topic Implementing AI/ML on KW45B41Z-EVK in Generative AI & LLMs

Implementing AI/ML on KW45B41Z-EVK

Re: Implementing AI/ML on KW45B41Z-EVK