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OpenAI's purpose-built speech-to-text model for converting audio into text transcripts, now in its deprecation window.
Overview. GPT-4o Transcribe is OpenAI's purpose-built speech-to-text model, built on the GPT-4o architecture and released in March 2025. Unlike the general-purpose gpt-4o chat model, it accepts audio input and returns a text transcript, making it a dedicated choice for teams adding voice input to an existing text-based application. It is served exclusively through Inference on OpenAI's proprietary stack.
Key strengths. OpenAI built this model on audio-centric pretraining data specifically to handle heavy accents, noisy rooms, and varying speech speeds better than the earlier Whisper models. Its single-step audio-to-text task fit means transcription happens directly, without multi-step reasoning or tool use in the loop. Output is consistently returned as syntactically valid JSON, which suits programmatic pipelines that need a predictable transcript format.
When to use it. Reach for this model when you need to convert spoken audio, such as calls or meetings, into text and don't need speaker diarization. It also supports OpenAI's Realtime API for low-latency streaming transcription, though OpenAI now recommends its newer gpt-live-transcribe model for new real-time streaming integrations. It is not a fit for chat, reasoning, coding, or any task requiring text or image input alongside audio.
Limitations. OpenAI has deprecated this model, with a scheduled shutdown date, and explicitly advises against using it for new integrations in favor of gpt-transcribe and gpt-live-transcribe. Its context window (16,000 tokens) and maximum output (2,000 tokens) are considerably smaller than the base gpt-4o model, and it only supports JSON as an output format. Its training data has a mid-2024 cutoff, and OpenAI has not disclosed parameter count, architecture details, or tokenizer specifics for this variant.
Sovereignty note. GPT-4o Transcribe is built by OpenAI, a US company, so data sent to this endpoint carries CLOUD Act exposure rather than Sovereign, EU-only handling. This is a relevant consideration for regulated buyers with strict data residency requirements.
| Inference Provider | Sovereignty | Runs in | Price | Status | Pin |
|---|---|---|---|---|---|
| L0 | €0.00539 per audio minute | Online |
2 use cases classified by the curator. The note says why.
Purpose-built transcription variant in the GPT-4o family, specifically trained for speech-to-text conversion — this is its core designed function.
Transcription-focused model can convert meeting audio to text as an input step, though it lacks native summarization capability flagged in its profile and would need pairing with a text model for the summary itself.
Sourced numbers, not our own evaluations. Percentiles are against the transcription models on Stav.
No benchmark source yet
curl https://api.stav.ai/v1/audio/transcriptions \
-H "Authorization: Bearer $STAV_API_KEY" \
-F model="openai/gpt-4o-transcribe" \
-F file="@meeting.mp3"→ X-Stav-Request-Id · X-Stav-Model · X-Stav-Provider → X-Stav-Sovereignty-Level — the rung the request was served at