Model detail
GPT-4o Transcribe Diarize
An OpenAI transcription model with speaker diarization, producing text while identifying which speaker spoke each segment.
Model specs
- Model ID
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gpt-4o-transcribe-diarize
- Context length
- 16K
- Max output
- 2K
- I/O modalities
- Released
- 2026-10
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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?
An OpenAI transcription model with speaker diarization
An OpenAI transcription model with speaker diarization, producing text while identifying which speaker spoke each segment.
What should you check before using it?
Confirm audio formats, sample rates, and pricing
GPT-4o Transcribe Diarize supports streaming and the OpenAI SDK. Knowledge cutoff: 2024-06-01. 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 Diarize client
MixRoute serves GPT-4o Transcribe Diarize 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-diarize and re-run your integration tests.
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Capabilities & compatibility
Unconfirmed capabilities stay "Unknown," no guesses
Streaming
GPT-4o Transcribe Diarize supports streamed responses.
stream: true streams tokens incrementally, so chat UIs render as they arrive.
OpenAI SDK
Call GPT-4o Transcribe Diarize 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 Diarize is an automatic speech recognition model with built-in speaker diarization. It associates audio segments with different speakers in a conversation.
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.