NPU Deployment Issue — Whisper Model (Genio 510)

NeuroPilot NeuroPilot - Analytical AI
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Hi,
I’m trying to deploy the Whisper model on the MediaTek Genio 510 NPU (MDLA), and I’m stuck at the final step. Below is the exact workflow I followed and where I’m blocked.

Steps Completed So Far

  1. Downloaded the Whisper PyTorch model (.pt) and converted the encoder to TFLite using mtk_pytorch_converter.

  2. Could not convert both encoder + decoder into a single TFLite file (as expected, Whisper decoder is not supported for full TFLite conversion).

  3. Quantized the TFLite encoder using calibration data with mtk_pytorch_converter.

  4. Generated the .dla model using:
    ncc-tflite --arch=mdla3.0

  5. Now I have a Whisper encoder in DLA format and I want to execute it on the Genio 510 board’s NPU.

Where I’m Stuck — Step 5

I don’t know how to actually run the .dla file on the Genio 510 board.

My Questions

1) To run a .dla model on the MDLA NPU, do I need to use the C++ Runtime API from the SDK?

The only available API I see in the SDK is the NeuroPilot Runtime API, which seems to be C++ oriented.

2) Can I run the DLA model using Python?

Or is Python completely unsupported for MDLA inference?
If Python is not possible, do I need to move my entire encoder-inference logic to C++ using the runtime SDK?

Summary of What I Want

I want to load and run my Whisper encoder DLA model on the Genio 510 NPU.
I need guidance on how to execute a .dla file — using Python or C++, and what the recommended method is.

If you have any suggestions or a proper workflow, I would be truly grateful.