GPT-4o Transcribe — OpenAI's Audio Transcription Model 📝🖼️🔢 → 📝
GPT-4o Transcribe is OpenAI's latest audio transcription model. Run it on Replicate to transcribe audio files without setting up OpenAI API keys or managing GPU infrastructure.
About
GPT-4o Transcribe converts speech to text using OpenAI's multimodal architecture. It handles multiple languages, accents, background noise, and overlapping speakers better than earlier Whisper-based models.
The model produces accurate transcriptions with proper punctuation and formatting, making it practical for meeting notes, podcast transcripts, subtitle generation, and voice-to-text workflows.
Typical use cases
- Transcribing meetings, interviews, and calls
- Generating subtitles for video content
- Converting voice memos to searchable text
- Processing multilingual audio in a single pipeline
Example Output
Output
So we just added GPT-4o transcribe to Replicate and thought you'd want to know. It's basically a speech-to-text model that uses GPT-4o to turn your audio into text. The cool thing is that it's noticeably better than the Whisper models we've been using, fewer errors, better at recognizing different languages, and just more accurate overall. If you've ever been frustrated with transcripts that mess up technical terms or struggle with different accents, you'll probably appreciate this upgrade. It just works better. Some quick tech specs if you're curious. It has a 16,000 token context window, which means it can handle longer audio clips in one go. And it can output up to 2,000 tokens, so you'll get nice complete transcripts. The model's knowledge is current up to June 2024, so it's pretty up-to-date with language and terminology.
Performance Metrics
2.89s
Prediction Time
2.90s
Total Time
All Input Parameters
{
"language": "en",
"audio_file": "https://replicate.delivery/xezq/XoxHeakty0z3KKc46cMLPKC2ct54ekT3EtvcwDQuRIuxfJdpA/tmpsglqtqn5.mp3",
"temperature": 0
}
Input Parameters
- prompt
- An optional text to guide the model's style or continue a previous audio segment. The prompt should match the audio language.
- language
- The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.
- audio_file (required)
- The audio file to transcribe. Supported formats: mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm
- temperature
- Sampling temperature between 0 and 1
Output Schema
Output
Example Execution Logs
Input audio duration: 54.756 seconds Input token count: 912 Output token count: 174 Total token count: 1086 TTFT: 1.38s
Version Details
- Version ID
cc7638666fc85e9defb010d99e304c0c0e94dcdbd3d31385f28f2730b4cdcc6d- Version Created
- November 7, 2025