Whisper‑Medium‑En is the advanced English-only variant in OpenAI’s Whisper series, with around 769 million parameters and optimized for English speech recognition tasks. Built on a Transformer encoder–decoder architecture, it is trained on 680k hours of speech (including English) and supports audio segments up to 30 seconds, delivering robust and accurate transcription performance.

• Model Size: Approximately 769M parameters, with both encoder and decoder models sized around 769 MB and 726 MB respectively
• Inference Speed: Approximately 0.51 inferences/second on Qualcomm Snapdragon hardware, with throughput between 249–299 MB/s
• Ideal Use Cases: Suitable for real-time captioning, long-form transcription, meeting notes, and smart assistants—especially on mid to high-end devices where noise robustness and accuracy are critical

The source model can be found here

When the user has fine-tuned the source model, the model conversion process must be performed again.

Users can refer to either of the following two methods to complete the model conversion:

• Using AIMO for model conversion: Click Model Conversion Reference in the Performance Reference section on the right to view the conversion steps.

• Using Qualcomm QNN for model conversion: Please refer to the Qualcomm QNN Documentation.

The model performance benchmarks and example code provided by Model Farm are all implemented based on the APLUX AidLite SDK.

For models in .bin format, you can use either of the following two inference engines to run inference on Qualcomm chips:

Inference using APLUX AidLite: please refer to the APLUX AidLite Developer Documentation

Inference using Qualcomm QNN: Please refer to the Qualcomm QNN Documentation

Inference Example Code

The inference example code is implemented using the AidLite SDK.

Click Model & Code to download the model files and the inference code package. The file structure is as follows:

/model_farm_{model_name}_aidlite
    
    |__ models # folder where model files are stored

    |__ python # aidlite python model inference example

    |__ cpp # aidlite cpp model inference example

    |__ README.md