How to Transcribe Audio for Free using OpenAI Whisper (The Unlimited Guide)

How to Transcribe Audio for Free using OpenAI Whisper

Transcription services charge $1 per minute. Otter.ai has monthly limits. OpenAI Whisper is free, unlimited, and more accurate than most humans. Here is how to run it on your own computer.

If you are a content creator, journalist, or developer, you know the pain of transcribing audio. You either spend hours typing it out yourself, or you pay expensive services to do it for you.

In late 2022, OpenAI open-sourced Whisper, a general-purpose speech recognition model. It was trained on 680,000 hours of multilingual data. It is, frankly, incredible. And because it is open-source, you can run it locally on your laptop for $0.

Privacy Note: When you run Whisper locally, your audio data never leaves your computer. This is crucial for confidential meetings or legal work.

Step 1: The Prerequisites

Whisper is a Python library. You don't need to be a coding wizard, but you do need two things installed:

1. Python 3.9+ (Download from python.org).
2. FFmpeg (A tool for handling audio files).

Step 2: Installing Whisper

Open your terminal (Command Prompt or PowerShell) and run this single command:

pip install -U openai-whisper

This downloads the library and its dependencies (like PyTorch). It might take a minute.

Step 3: Transcribing Your First File

You don't even need to write a script. You can use the Command Line Interface (CLI). Navigate to the folder containing your audio file (e.g., `interview.mp3`) and run:

whisper interview.mp3 --model base

Whisper will start processing. You will see the text appearing in the terminal as it works. When it finishes, it will save the transcript in multiple formats (TXT, SRT for subtitles, VTT) right in your folder.

Choosing the Right Model

Whisper comes in five sizes. The tradeoff is always Speed vs. Accuracy.

Model	VRAM Required	Speed	Accuracy
Tiny	~1 GB	Lightning Fast	Low
Base	~1 GB	Fast	Good (Standard)
Small	~2 GB	Moderate	Very Good
Medium	~5 GB	Slow	Excellent
Large	~10 GB	Very Slow	Near Human

Recommendation: For most users, the `small` or `medium` models offer the best balance. If you have a powerful GPU (NVIDIA), use `medium`. If you are on a standard laptop CPU, stick to `base`.

Step 4: Using Python (For Automation)

If you want to build a tool that auto-transcribes every file in a folder, you can use a Python script:

import whisper model = whisper.load_model("base") result = model.transcribe("audio.mp3") print(result["text"])

That is 3 lines of code to unlock powerful AI speech-to-text. You can loop this over thousands of files and create a searchable database of your entire audio library.

Conclusion

Paying for transcription in 2026 is a "lazy tax." With 5 minutes of setup, you can have a world-class transcription studio running on your laptop for free, forever.

Stop renting AI. Start owning it.

Download January Skills: Whisper Setup Guide & Batch Script