Is the Whisper AI model safe to download and run on your own computer?

Yes, the Whisper model is safe to download and run for private audio when you take it from the official project and run it on a computer you control. OpenAI published the code and the model weights for anyone to use, and a copy running on your own machine does not send your recordings to OpenAI. The remaining risks sit around the model: the file you load, the software that loads it, and any app that wraps it. Each one has a check you can run in minutes.

OpenAI released the model under a license that allows local use

OpenAI released Whisper's code and model weights under the MIT License ¹. That license allows anyone to use, copy and modify the software, so nothing in its terms requires you to send audio back to OpenAI. A license answers a legal question, though, not a safety one. It says what you may do with the files, not that a particular download is free of tampering or defects. The safety comes from where you get the files and what you run them with.

The model file is checked against a checksum, but the checksum ships with it

The openai-whisper loader downloads a model from a download address the first time you load it by name. It takes the expected SHA256 checksum from that address and compares it with the hash of the file it saved ². When the hashes do not match, the loader downloads the file again ³.

That check catches a corrupted download or a file that changed in transit. It cannot catch a compromised package, because the expected checksum is written into the same package you installed. If someone altered the package, they could alter the checksum with it. Your protection against that comes from the source. Install using the instructions in the project's README, and avoid model files from forum posts or mirrors you cannot identify.

A model file is loaded like code, so it needs the same care

Whisper's model files are PyTorch checkpoints, and the loader calls torch.load with weights_only set to True on PyTorch 1.13 and later ⁴. That setting restricts what the loader will unpickle, which is a real safeguard. It is not a guarantee. PyTorch's own documentation says the function uses an unpickler and warns that users should "Never load data from an untrusted source." ⁵

In practice, a model file from an unknown mirror deserves the same caution as any program you download from an unverified site. Use the download route that the app or the project documents, and keep the model in a folder you control.

Running the model on your machine keeps audio on that machine

A local copy needs no server to transcribe. The whisper.cpp project shows Whisper running fully offline and on a device, in a demonstration on an iPhone 13 ⁶. A demonstration shows the design works, not how your computer will perform, so test your own setup. The model needs a connection once, for the download. After that, transcription needs no network, and our answer on whether Whisper runs offline walks through the steps.

The command-line tool also needs ffmpeg, a separate program that you install from your system's package manager ⁷. Install it the same careful way you install the model, and check its source as well.

Some apps named after Whisper send audio to the cloud

The model and the apps built on it are separate things. Superwhisper, for example, offers a Pro plan that adds cloud models and AI processing ⁸, so the plan and mode you choose decide where your audio goes. The model can be safe while an app built on it sends your audio elsewhere.

Check each app's settings for a cloud mode or a field for an API key, then run the airplane-mode test on a real recording. Our question on whether Whisper apps send audio to OpenAI gives the four checks in order.

Whisper can invent text, which is a risk to the transcript

Safe use also means checking the output. Whisper can produce text that nobody said. In a 2024 study, roughly 1 percent of Whisper audio transcriptions contained entire hallucinated phrases or sentences that did not exist in the audio ⁹. That study used one dataset and an earlier model, so the rate on your recordings may be different.

Keeping the files on your own computer does not make an invented sentence accurate. Compare each transcript with its audio before you file it or share it. Our question on why Whisper hallucinates explains where the invented text comes from.

What to do before you run Whisper on private audio

1. Download from the official source. Install with the project's own instructions, and skip model files from forums and unknown mirrors.
2. Install ffmpeg from your system's package manager. Do not use a copy someone sent you.
3. Load the model once while you are online. The file is saved, and later runs use the saved copy.
4. Run the airplane-mode test on a real recording. Text that appears with the network off was produced on your device.
5. Read the app's settings. Look for an API key field or a cloud mode, and turn off any option you did not choose.
6. Review each transcript against its audio before you rely on it.

For the full picture, including the hosted API and the cases where a local setup is not enough, read the guide to whether Whisper AI is safe. The overview of speech to text privacy covers the other places your words can go. For the term, see on-device speech recognition. If you use the hosted API instead, our answer on whether OpenAI stores Whisper audio covers retention, and whether offline Whisper needs an OpenAI API key covers the key.