Model detail
GPT-4o Transcribe
OpenAI's GPT-4o-based transcription model, designed to improve speech-recognition accuracy, word error rate, and language recognition compared with original Whisper models.
Model specs
- Model ID
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gpt-4o-transcribe
- Context length
- 16K
- Max output
- 2K
- I/O modalities
- Released
- 2025-03
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API endpoints
One MixRoute gateway, OpenAI-compatible
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OpenAI-compatible
/v1/chat/completionsPOST
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Pricing
Flat rate, unit: /1M Tokens
Input
$2.5000 /1M Tokens
Completion
$10.0000 /1M Tokens
Audio input
$6.0000 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
OpenAI's GPT-4o-based transcription model
OpenAI's GPT-4o-based transcription model, designed to improve speech-recognition accuracy, word error rate, and language recognition compared with original Whisper models.
What should you check before using it?
Confirm audio formats, sample rates, and pricing
GPT-4o Transcribe supports streaming and the OpenAI SDK. Knowledge cutoff: 2024-06-01. Released 2025-03-20. It is billed at 2.5 USD per 1M tokens. Test a representative workload before production.
Why use it through MixRoute?
Swap the base URL, keep the GPT-4o Transcribe client
MixRoute serves GPT-4o Transcribe on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID gpt-4o-transcribe and re-run your integration tests.
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Capabilities & compatibility
Unconfirmed capabilities stay "Unknown," no guesses
Streaming
GPT-4o Transcribe supports streamed responses.
stream: true streams tokens incrementally, so chat UIs render as they arrive.
OpenAI SDK
Call GPT-4o Transcribe through MixRoute's OpenAI-compatible endpoint.
base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.
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Token cost estimator
Live estimate from this page's pricing, not an actual bill
This model has no cache-read price; caching is not counted
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FAQ
GPT-4o Transcribe is a speech-to-text model that uses GPT-4o to transcribe audio. It offers improvements to word error rate and better language recognition compared to the original Whisper model.
One endpoint, a testable decision
Test this model and alternate routes with the same request format
Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.