Whisper-1
Whisper-1 is OpenAI's speech-to-text model that transcribes and translates audio at $0.006 per minute.
Automatic speech recognition and transcription
Whisper-1 is a speech recognition model developed by OpenAI and released in September 2022. It is trained on a large dataset of multilingual and multitask supervised data collected from the web, enabling it to transcribe audio in multiple languages and translate speech into English. The model is available as an open-source release and is also accessible via OpenAI's API under the identifier whisper-1.
Whisper-1 is designed for tasks that require converting spoken audio into written text, including transcription of interviews, meetings, podcasts, and voice memos. It accepts audio input and returns text output, making it straightforward to integrate into applications that need automated captioning or voice-to-text functionality. At $0.006 per minute of audio processed, it is positioned as a low-cost option for audio transcription workloads.
What Whisper-1 supports
Audio Transcription
Converts spoken audio into written text. Supports a wide range of audio formats including mp3, mp4, wav, and webm.
Speech Translation
Translates spoken audio from multiple languages into English text in a single pass, without requiring a separate translation step.
Multilingual Support
Recognizes and transcribes speech across dozens of languages, trained on multilingual audio data collected from the web.
Open Source Weights
The underlying Whisper model weights are publicly available on GitHub, allowing self-hosted deployment outside of the API.
Low-Cost Pricing
Billed at $0.006 per minute of audio, making it cost-effective for high-volume transcription workloads.
Timestamp Output
Can return word- or segment-level timestamps alongside transcribed text, useful for subtitle generation and audio alignment.
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Get Started FreeCommon questions about Whisper-1
How is Whisper-1 priced?
Whisper-1 is priced at $0.006 per minute of audio submitted for transcription or translation.
Does Whisper-1 have a context window?
Whisper-1 is a speech-to-text model and does not use a token-based context window in the same way language models do. Audio inputs are processed in segments, with a practical limit of around 25 MB per file via the OpenAI API.
What audio file formats does Whisper-1 accept?
Whisper-1 supports several common audio and video formats including mp3, mp4, mpeg, mpga, m4a, wav, and webm.
Can Whisper-1 translate audio into English?
Yes. In addition to transcription, Whisper-1 supports a translation mode that converts spoken audio in supported languages directly into English text.
Is the Whisper model open source?
Yes. OpenAI released the Whisper model weights and code publicly. The whisper-1 identifier refers to the version hosted on OpenAI's API, but the underlying model is available on GitHub for self-hosted use.
What people think about Whisper-1
Community discussion around Whisper is limited in the provided threads, with only one directly relevant post covering an open-source GUI called EasyWhisperUI that adds cross-platform GPU support for running Whisper locally on Windows and Mac. That thread attracted modest engagement, suggesting a niche but active audience of developers interested in self-hosted transcription workflows.
The other thread found is unrelated to Whisper and concerns a different model entirely. No significant community concerns or limitations specific to Whisper were surfaced in these threads.
Claude Code is a Beast – Tips from 6 Months of Hardcore Use
EasyWhisperUI - Open-Source Easy UI for OpenAI’s Whisper model with cross platform GPU support (Windows/Mac)
Documentation & links
Parameters & options
Add per-word start/end times and confidence inside each transcript segment. Increases the size of the result considerably.
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