---
title: "OpenAI whisper-1 shutdown: migration guide and alternatives"
description: "OpenAI removes whisper-1 from its API on Feb 26, 2027. How to move to gpt-transcribe, and what to do about SRT, timestamps and translation."
url: https://exemplary.ai/blog/openai-whisper-1-api-shutdown
published: 2026-08-28
updated: 2026-09-30
author: "Sarath Chandran"
publisher: "Exemplary AI (https://exemplary.ai)"
---

# OpenAI whisper-1 shutdown: migration guide and alternatives

OpenAI plans to remove `whisper-1` from its API on February 26, 2027. It told developers on August 26, 2026, and the same notice covers `gpt-4o-transcribe`, `gpt-4o-mini-transcribe` and `gpt-4o-transcribe-diarize`. For all four, OpenAI names `gpt-transcribe` (recorded files) or `gpt-live-transcribe` (live audio) as the replacement ([OpenAI deprecations](https://developers.openai.com/api/docs/deprecations)). If you only need plain transcription, switching is mostly a one-line model change on the same endpoint. The hard part is everything else `whisper-1` does: SRT and VTT subtitles, word and segment timestamps, and translation into English. OpenAI's migration guide says to keep `whisper-1` for those, and as of September 30, 2026 its docs name no replacement for them. Only the hosted API model is affected. The open-source Whisper model stays free to download and run.

## What's being removed, and when

| Model | What it does now | Price per minute | Named replacement |
| --- | --- | --- | --- |
| `whisper-1` | Transcription, SRT/VTT output, timestamps, translation into English | $0.006 | `gpt-transcribe` or `gpt-live-transcribe` |
| `gpt-4o-transcribe` | Transcription (JSON only) | $0.006 | `gpt-transcribe` or `gpt-live-transcribe` |
| `gpt-4o-mini-transcribe` | Lower-cost transcription (JSON only) | $0.003 | `gpt-transcribe` or `gpt-live-transcribe` |
| `gpt-4o-transcribe-diarize` | Transcription with speaker labels | $0.006 | `gpt-transcribe` or `gpt-live-transcribe` |

Prices are OpenAI's per-minute estimates from its [pricing page](https://developers.openai.com/api/docs/pricing), checked September 30, 2026. The two dates to know:

- **August 26, 2026:** OpenAI "notified developers using `whisper-1`, `gpt-4o-transcribe`, `gpt-4o-mini-transcribe`, and `gpt-4o-transcribe-diarize` of their deprecation."
- **February 26, 2027:** the planned removal from the API. Assume any request that still names one of these models will stop working that day.

## The replacements: gpt-transcribe and gpt-live-transcribe

OpenAI released both models on July 29, 2026 ([OpenAI Developer Community](https://community.openai.com/t/gpt-live-transcribe-and-gpt-transcribe-two-new-transcription-models-in-the-api/1388318)).

- **`gpt-transcribe`** is for completed audio: uploaded files, streamed transcripts of a finished file, and committed turns in a Realtime session over WebSocket. It costs $0.0045 per minute ([model page](https://developers.openai.com/api/docs/models/gpt-transcribe)). OpenAI's speech-to-text guide calls it "the recommended model for transcribing recorded speech in its original language."
- **`gpt-live-transcribe`** is for audio that is still arriving, like a microphone, a call or a live stream. It runs in Realtime transcription sessions over WebSocket or WebRTC and costs $0.017 per minute ([model page](https://developers.openai.com/api/docs/models/gpt-live-transcribe)).

The file limits don't change. Uploads are capped at 25 MB, and the accepted formats are mp3, mp4, mpeg, mpga, m4a, wav and webm ([OpenAI speech-to-text guide](https://developers.openai.com/api/docs/guides/speech-to-text)).

## How to migrate a plain transcription call

OpenAI's [migration cookbook](https://developers.openai.com/cookbook/examples/migrating_from_whisper_to_gpt_transcribe) keeps the endpoint (`POST /v1/audio/transcriptions`) and the file upload. What changes is the model name, some request fields and the response.

1. **Change the model.** Replace `whisper-1` with `gpt-transcribe`.
2. **Read the new response.** You get JSON with `text` and a `languages` array of detected languages. An empty array (`"languages": []`) is a valid result that means the model couldn't make a reliable prediction. It isn't an error.
3. **Swap `language` for `languages`.** The new model takes an array of expected languages. Don't send both fields.
4. **Move vocabulary into `keywords`.** Use `prompt` for free-form context about the recording and `keywords` for literal terms you expect to hear, such as product names or account IDs. Each keyword must be a single line without `<`, `>` or line breaks. One invalid keyword makes the API reject the whole request.
5. **Turn on streaming if you want partial text.** Set `stream=true` with `gpt-transcribe` to receive `transcript.text.delta` events while it works. `whisper-1` ignores `stream`.
6. **Test on your own audio.** The cookbook suggests comparing word error rate plus exact-match accuracy on names, numbers and email addresses. It also suggests checking that hinted keywords don't appear in the transcript when nobody said them.

A minimal request looks like this:

```bash
curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F file="@meeting.mp3" \
  -F model="gpt-transcribe" \
  -F 'languages[]=en' \
  -F 'keywords[]=AC-42' \
  -F 'prompt=A customer support call about a premium plan.'
```

## What has no drop-in replacement

The cookbook's compatibility section warns that some `whisper-1` features "do not have a drop-in replacement in `gpt-transcribe` or `gpt-live-transcribe`." Here's where each one stands in OpenAI's docs as of September 30, 2026:

| Feature | How you get it today | What OpenAI's docs say to do | After February 26, 2027 |
| --- | --- | --- | --- |
| SRT or VTT subtitles | `whisper-1` with `response_format=srt` or `vtt` | Keep `whisper-1`, or build and test your own conversion | No named successor |
| Word or segment timestamps | `timestamp_granularities[]`, "only supported for `whisper-1`" | Keep a model that supports timestamps | No named successor |
| Translation into English | `/v1/audio/translations` with `whisper-1` | Keep the translations endpoint with a supported model | No named successor |
| Speaker labels | `gpt-4o-transcribe-diarize` with `diarized_json` | Use `gpt-4o-transcribe-diarize` | That model is also being removed |

Building your own subtitles from `gpt-transcribe` isn't simple either. Its documented response contains text and detected languages, but no timestamps, so there's nothing to time the captions against. OpenAI's pricing page also lists a live translation model, `gpt-realtime-translate` ($0.034 per minute). It's a Realtime model, not a stand-in for the file-based translations endpoint.

OpenAI may add these features before the deadline. Check the [deprecations page](https://developers.openai.com/api/docs/deprecations) and the [speech-to-text guide](https://developers.openai.com/api/docs/guides/speech-to-text) before you rebuild anything.

## Options for subtitles, timestamps and translation

### 1. Keep whisper-1 until the deadline

It still works, and the cookbook recommends it for these jobs. It buys time, not a solution: plan a fallback before February 2027.

### 2. Run open-source Whisper yourself

The deprecation covers API models. Whisper itself stays on [GitHub](https://github.com/openai/whisper) under the MIT License. OpenAI's API reference says `whisper-1` "is powered by our open source Whisper V2 model," so self-hosting `large-v2` keeps you on the same model family. The command-line tool writes `txt`, `vtt`, `srt`, `tsv` and `json`, and it has experimental word timestamps. It translates into English with the multilingual models; the default `turbo` model isn't trained for translation, so use `medium` or `large`. The costs are your own hardware, a GPU for any real speed, and the upkeep. Our [OpenAI Whisper guide](https://exemplary.ai/blog/openai-whisper) covers setup and model choice.

### 3. Switch to another speech-to-text API

Two examples with subtitle output, per their own docs and pricing pages (checked September 30, 2026):

- **AssemblyAI** has [endpoints that return SRT or VTT](https://www.assemblyai.com/docs/api-reference/transcripts/get-subtitles) for a finished transcript, with an optional characters-per-caption limit. Pre-recorded pricing starts at $0.15 per hour for Universal-2 (about $0.0025 per minute). Universal-3.5 Pro costs $0.21 per hour, and speaker labels add $0.02 per hour ([AssemblyAI pricing](https://www.assemblyai.com/pricing)).
- **Deepgram** returns JSON with timestamps. Its open-source caption packages for JavaScript and Python [convert that JSON into WebVTT or SRT](https://developers.deepgram.com/docs/automatically-generating-webvtt-and-srt-captions). Nova-3 costs $0.0043 per minute for one language and $0.0052 per minute multilingual, with speaker diarization included on pay-as-you-go ([Deepgram pricing](https://deepgram.com/pricing)).

We haven't compared their translation features or accuracy, so test them on your own audio. For a wider field, see our [transcription software comparison](https://exemplary.ai/blog/best-transcription-software-2025).

### 4. If you called whisper-1 only to caption your own videos

If the API was just a quick way to get transcripts or subtitles for your own recordings, a hosted editor may be less work than a migration. Disclosure: we make Exemplary AI. It [transcribes](https://exemplary.ai/transcription) audio and video in 99 languages, lets you fix the text in an editor, exports SRT, VTT or TXT files, and can translate the result. If you're not sure which subtitle format you need, see [SRT vs VTT](https://exemplary.ai/blog/srt-vs-vtt).

## What switching costs

Here's what 1,000 hours of audio (60,000 minutes) costs at OpenAI's list prices:

| Model | Price per minute | 1,000 hours |
| --- | --- | --- |
| `whisper-1` | $0.006 | $360 |
| `gpt-4o-transcribe` | $0.006 | $360 |
| `gpt-4o-mini-transcribe` | $0.003 | $180 |
| `gpt-transcribe` | $0.0045 | $270 |
| `gpt-live-transcribe` | $0.017 | $1,020 |

Moving from `whisper-1` to `gpt-transcribe` cuts the per-minute price by a quarter. Moving from `gpt-4o-mini-transcribe` raises it by half. Moving batch jobs to `gpt-live-transcribe` makes little sense: it's built for live audio and costs almost four times as much.

## A migration checklist

1. **Find every call.** Search your code and config for `whisper-1`, `gpt-4o-transcribe`, `gpt-4o-mini-transcribe` and `gpt-4o-transcribe-diarize`.
2. **Label each one by what it needs:** plain text, subtitles, timestamps, translation, speaker labels or live audio.
3. **Move the plain-text calls to `gpt-transcribe` now.** Change the language and keyword fields and test them with your own audio.
4. **Move live captioning to `gpt-live-transcribe`.** Keep your existing Realtime session code, and tune the model's `delay` setting to trade speed against accuracy.
5. **Choose a path for the rest:** keep `whisper-1` for now, self-host Whisper, or change providers.
6. **Pick an internal deadline weeks before February 26, 2027**, and recheck OpenAI's deprecations page as it gets closer.

## FAQ

### When is OpenAI shutting down whisper-1?

OpenAI plans to remove `whisper-1` from the API on February 26, 2027. It announced the deprecation on August 26, 2026.

### Is open-source Whisper being discontinued?

No. The notice lists hosted API models only. The open-source Whisper code and weights remain on GitHub under the MIT License.

### What replaces whisper-1?

OpenAI names `gpt-transcribe` for recorded audio and `gpt-live-transcribe` for live audio. Both use the existing transcription endpoints.

### Does gpt-transcribe support SRT, VTT or timestamps?

Not according to OpenAI's docs as of September 30, 2026. The migration guide says to keep `whisper-1` for native SRT and VTT output, and timestamp granularities are documented only for `whisper-1`.

### Is gpt-transcribe cheaper than whisper-1?

Yes. It costs $0.0045 per minute, compared with $0.006 for `whisper-1`. It is more expensive than `gpt-4o-mini-transcribe` at $0.003, which is also being removed.

> Exemplary AI is a browser-based AI tool that turns long videos and recordings into short captioned clips, transcripts in 99 languages, subtitles, translations into 116 languages, and written posts such as summaries, blog posts and YouTube chapters. It is built for YouTubers, podcasters and marketing teams; the Free plan includes 500 one-time credits with watermarked video exports. Pricing: https://exemplary.ai/pricing