What file formats, languages, and output options does WhisperAPI support?

WhisperAPI accepts both audio and video files—either uploaded directly or passed as remote URLs—transcribes them in 98+ languages, and lets you download the result as JSON, TEXT, VTT, DOCX, or PDF. You can also pick between different Whisper model sizes to trade speed against accuracy. The service is built on OpenAI Whisper and offers both a REST API and a no-code dashboard, so the same capabilities are available whether you integrate programmatically or work through the browser.

Input: what you can send

WhisperAPI handles two input methods:

• Direct file uploads — send a local audio or video file in the request.
• Remote URLs — point the API at a file hosted elsewhere instead of uploading it.

Both audio and video files are processed through the same API, so you don't need separate endpoints or pipelines for each media type. The site states file uploads are supported up to 10GB, with no minute limits on transcription duration.

Languages

WhisperAPI supports 98+ languages, described as covering all major languages with high accuracy. Because it runs on OpenAI Whisper, language coverage follows that engine's multilingual capability. You can also pass a language parameter in the API request (for example, language=en) to specify the expected language rather than relying on detection.

Output formats

Transcripts can be generated, previewed, and downloaded in multiple formats. The formats shown on the site are:

In the API, the output format is set with the format parameter (for example, format=srt in the documented example). The dashboard offers the same download options through its interface.

Choosing a model: speed vs accuracy

WhisperAPI lets you select between different Whisper models, which is the main lever for balancing turnaround time against transcription quality. The site's example uses model_size=large-v2, and its sample transcript was generated with the Whisper Large-v2 model. Larger models generally favor accuracy; smaller ones favor speed. The site advertises industry-leading 99.8% accuracy across audio types and results "in minutes, not hours."

Using the API

The documented request pattern is a curl call with form fields for the file, language, format, and model size, plus an API key header:

curl \
  -F "[email protected]" \
  -F "language=en" \
  -F "format=srt" \
  -F "model_size=large-v2" \
  -H "X-API-Key: YOUR_API_KEY" \
  https://api.whisper-api.com/transcribe

• Input: the file (or a remote URL), plus optional language, format, and model_size fields.
• Action: the API sends the media to the selected Whisper model for transcription.
• Expected result: a transcript returned in your chosen format, downloadable or consumable programmatically.

The site also notes you can fine-tune model parameters for specific use cases, and that files auto-delete after 24 hours.

No-code alternative

If you don't want to write code, the dashboard provides a drag-and-drop interface with real-time transcription progress, multi-format downloads, and a single place to manage all transcriptions. The output formats and language support are the same as the API's.

Getting started

The site advertises a free start with 5 transcription credits and states no credit card is required to begin. Beyond that, pricing is pay-as-you-go, with Paddle listed as the payment platform. For current rates and credit details, check the pricing page directly, since specific prices aren't stated in the material summarized here.