What Is OpenAI Whisper — and How Do You Use It?

Whisper is a speech-to-text model built by OpenAI that listens to an audio file and turns it into a written transcript — automatically detecting which language is being spoken and, if you want, translating it into English. OpenAI released it as free, open-source software in September 2022, so anyone can download and run it without paying anything, while OpenAI also sells a hosted version through its paid API for people who’d rather not manage the software themselves. It covers close to 100 languages, including Georgian, which makes it one of the few speech recognition systems that works reasonably well outside English, Spanish, or Mandarin. Whisper handles the “listening” half of voice AI; on the “speaking” half, tools like ElevenLabs turn text back into audio.

Beyond plain transcription, Whisper can also translate: point it at a recording in, say, French or Japanese, and it can output an English transcript directly, skipping a separate translation step. It cannot yet translate between two non-English languages in one pass — only into English.

What You Need

How you use Whisper depends on how much setup you want to do:

• No coding at all: a number of transcription, subtitling, and note-taking apps run Whisper behind the scenes, so you just upload an audio file through their interface.
• Free, local, and private: Whisper’s code and model weights are released under the MIT License, so anyone can install it and transcribe audio on their own machine — nothing has to leave your computer. This route needs Python and the FFmpeg audio tool installed first.
• Paid, hosted, and easy to integrate: developers who want to add transcription to an app can call OpenAI’s API instead of running anything themselves — no local setup, no hardware to manage, but the audio does leave your machine and travel to OpenAI’s servers.

Step by Step

To run Whisper yourself, install FFmpeg for your operating system, then install the model with:

pip install -U openai-whisper

From there, one command transcribes a file: whisper audio.mp3 --model turbo. Whisper ships in six sizes, from tiny (fast, less accurate, runs on almost any laptop) to large (slower, most accurate, wants a decent graphics card); the turbo model is a sensible default, since it is nearly as accurate as large but noticeably faster.

To use OpenAI’s hosted version instead, create an OpenAI API account and follow the official speech-to-text guide, which walks through sending an audio file to an API endpoint and getting the transcript back as text. This costs money: as of September 2026, OpenAI’s original whisper-1 model is billed at $0.006 per minute of audio (about $0.36 per hour), with newer transcription models priced slightly differently, per OpenAI’s pricing page — worth checking before you build anything, since rates change.

Tips and Pitfalls

Whisper is generally accurate, but it has known quirks. It can “hallucinate” — inventing sentences that were never spoken — during long stretches of silence or background noise, so don’t treat its output as ground truth for anything important without a human check. Audio files larger than 25 MB need to be split before they can be uploaded to the API. And while Whisper’s transformer-based architecture was trained on 680,000 hours of audio scraped from the internet, less-represented languages received far less training data than English, so accuracy on languages like Georgian, while usable, won’t quite match English or Spanish. Choosing between the local and hosted routes is mostly a privacy-versus-convenience call: local Whisper keeps sensitive recordings — medical notes, legal calls, internal meetings — off any third-party server, while the API trades that away for zero setup.

Why It Matters for Georgia

Georgian is one of Whisper’s supported languages, listed under the code “ka” — a rare case of a major AI speech model working with the language directly, instead of requiring a detour through English. That makes it genuinely usable for Georgian meeting notes, subtitling, or dictation, and it pairs naturally with the growing set of AI translation tools that can take over once Whisper has turned Georgian speech into Georgian text.