# OpenAI whisper-1 Alternative — Speech-to-Text API (`dropin-apis/whisper-compat`) Actor whisper-1 alternative and speech-to-text API for apps that need SRT, VTT, or word timestamps: point the official OpenAI SDK at this host. OpenAI removes whisper-1 on 26 February 2027. $0.006 per minute, billed per started 15 seconds. - **URL**: https://apify.com/dropin-apis/whisper-compat.md - **Developed by:** [drop-in apis](https://apify.com/dropin-apis) (community) - **Categories:** AI, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 15 seconds of audios This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## OpenAI whisper-1 Alternative — Speech-to-Text API **whisper-1 alternative and speech-to-text API** that serves `POST /v1/audio/transcriptions` and `/v1/audio/translations` with `srt`, `vtt` and `verbose_json` word timestamps, using the official OpenAI SDKs. OpenAI removes whisper-1 on 26 February 2027 ([deprecations](https://developers.openai.com/api/docs/deprecations)). **At a glance:** **$0.006 per minute of audio** ($0.0015 per started 15 seconds; failed requests are not charged) · about 4 seconds of audio per second of compute (a 1-minute file returns in about 12 seconds) · `srt`, `vtt` and `verbose_json` output. Try it with no code: click **Start** with the prefilled sample URL (batch mode, billed at least 1 minute per file). Last updated: 2026-10-02 · **Full migration guide:** https://alidaram99.github.io/api-alternatives/whisper-1-alternative/ You change `base_url` and `api_key`, and keep the same multipart request and the same `json`, `text`, `srt`, `vtt` and `verbose_json` responses, including OpenAI's error format. - ✅ Same endpoints, form fields and response formats as whisper-1 - ✅ Word and segment timestamps (`timestamp_granularities[]`), SRT and VTT subtitles, `usage` in seconds - ✅ Translation to English (`/v1/audio/translations`) - ✅ 99 languages with auto-detection, the same set as Whisper - ✅ flac, m4a, mp3, mp4, mpeg, mpga, oga, ogg, wav, webm, up to 25 MB and 10 minutes per file - ✅ **$0.006 per minute, billed per started 15 seconds.** That is OpenAI's whisper-1 per-minute rate. OpenAI rounds to the second and we round up to 15 s, so very short clips cost slightly more here (see Pricing). - 🔒 Audio is processed in memory and never stored. No third-party API is called. ### Migrate in two lines Your endpoint is the Actor's Standby URL (on the Actor's **Standby** tab), for example `https://--whisper-compat.apify.actor`. Use your [Apify API token](https://console.apify.com/settings/integrations) as the API key. The OpenAI SDKs send it as `Authorization: Bearer …`, which is how Apify authenticates Standby requests. > Pass the token only as `api_key`. Don't append `?token=…` to `base_url`: the SDK adds the route after it, and the request ends up at the wrong URL. #### Python (`openai`) ```python import os from openai import OpenAI client = OpenAI( base_url="https://--whisper-compat.apify.actor/v1", # was: default api.openai.com api_key=os.environ["APIFY_TOKEN"], # was: your OpenAI key ) with open("meeting.mp3", "rb") as f: result = client.audio.transcriptions.create( model="whisper-1", file=f, response_format="verbose_json", timestamp_granularities=["word", "segment"], ) print(result.text) print(result.words[0], len(result.segments), "segments") ``` #### Node.js (`openai`) ```js import fs from 'node:fs'; import OpenAI from 'openai'; const client = new OpenAI({ baseURL: 'https://--whisper-compat.apify.actor/v1', apiKey: process.env.APIFY_TOKEN, }); const srt = await client.audio.transcriptions.create({ model: 'whisper-1', file: fs.createReadStream('talk.mp4'), response_format: 'srt', }); console.log(srt); ``` #### curl ```bash curl -s https://--whisper-compat.apify.actor/v1/audio/transcriptions \ -H "Authorization: Bearer $APIFY_TOKEN" \ -F model=whisper-1 \ -F response_format=vtt \ -F file=@interview.m4a ``` ### Response examples (real output) `response_format=json`: ```json { "text": "Mr. Quilter is the Apostle of the Middle Classes, and we are glad to welcome his Gospel. Nor is Mr. Quilter's manner less interesting than his matter.", "usage": { "type": "duration", "seconds": 12 } } ``` `response_format=srt` (NASA's public-domain Apollo 11 recording): ``` 1 00:00:00,000 --> 00:00:05,000 I'm going to step off the limb now. 2 00:00:15,000 --> 00:00:18,000 That's one small step for man. 3 00:00:20,000 --> 00:00:24,000 One giant leap for mankind. ``` `response_format=verbose_json` returns `task`, `language` (e.g. `"english"`), `duration`, `text` and `segments[]`. Each segment has `id`, `seek`, `start`, `end`, `text`, `tokens`, `temperature`, `avg_logprob`, `compression_ratio` and `no_speech_prob`. The response also includes `words[]` (`word`, `start`, `end`) when you ask for word timestamps, and `usage`. That is the same shape OpenAI documents. ### Compatibility | Feature | Status | |---|---| | `POST /v1/audio/transcriptions`, `POST /v1/audio/translations`, `GET /v1/models` | ✅ Same paths (also served without the `/v1` prefix) | | Fields `file`, `model` (`whisper-1`), `language`, `prompt`, `response_format`, `temperature`, `timestamp_granularities[]` | ✅ Same names, defaults and validation | | `json` (+ `usage`), `text`, `srt`, `vtt`, `verbose_json` (segments/words as requested) | ✅ Same shapes | | Error envelope `{"error":{"message","type","param","code"}}`, 400/413/429 | ✅ Same format. Unsupported file formats return OpenAI's exact message | | Transcription quality | ⚠️ Runs Whisper **small** (multilingual) with CTranslate2 int8 and beam search 5. OpenAI's whisper-1 is the much larger Whisper V2. On clean English speech we measured a **3.8% word error rate** (LibriSpeech). Expect more errors than whisper-1 on noisy audio, heavy accents and rare languages | | Files longer than 10 minutes | ❌ Rejected with `400 audio_too_long`. Split long recordings into chunks (OpenAI has a 25 MB cap anyway) | | `stream`, `include`, `chunking_strategy`, `diarized_json`, gpt-4o / gpt-transcribe models | ❌ Not supported (whisper-1 didn't support them either) | ### How it compares | Option | Same whisper-1 request and formats? | Price | Notes | |---|---|---|---| | **This Actor** | Yes: official OpenAI SDK, change `base_url` and `api_key` | $0.006/min, billed per started 15 s | Whisper small (about 4% word error on clean English); up to 10 min per file | | OpenAI whisper-1 | It is the original | $0.006/min | Removed 26 Feb 2027 | | OpenAI gpt-4o-transcribe / gpt-4o-mini-transcribe | No: OpenAI's API spec lists `json` as their only response format | OpenAI pricing | No SRT/VTT or word timestamps | | File-to-text transcriber Actors on Apify | No OpenAI SDK compatibility | Varies by Actor | Fine if you only need text from a file | ### Pricing **$0.0015 per started 15 seconds of audio, which is $0.006 per minute** (pay-per-event `audio-15s`). OpenAI billed whisper-1 at $0.006 per minute rounded to the second, so the two prices match on whole 15-second blocks. A clip shorter than 15 s costs $0.0015 here instead of about $0.001 at OpenAI. Examples: | Audio | Price | |---|---| | 10-second voice note | $0.0015 | | 1-minute clip | $0.006 | | 10-minute recording | $0.06 | Failed requests (bad format, too long, can't decode) are not charged. **Batch mode** (a list of `audioUrls`, see below) bills at least 1 minute ($0.006) per file, because each batch run starts a new container. Standby API requests have no minimum. Any additional platform charges, such as Apify's per-run start event, are listed on this Actor's **Pricing** tab and follow [Apify's pay-per-event terms](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event). **Spending limit.** If you set a maximum total charge on the run, a request whose audio would cost more than the remaining budget is refused *before* it is transcribed, with `429 insufficient_quota`, so no compute is spent on audio your budget can't cover. In batch mode the run stops cleanly at the limit and keeps the files transcribed so far. ### Speed and limits Each instance has 1 CPU core and processes about **4 seconds of audio per second of compute**. A 1-minute file returns in about 12 seconds and a 10-minute file in about 2.5 minutes. Requests to one instance are processed one at a time. When an instance is busy, it returns `429 rate_limit_exceeded`, which the OpenAI SDKs retry automatically, and Apify can start more instances. After about 5 minutes without requests the instance sleeps, and the next request waits a few extra seconds while it starts. ### Batch mode (no code) Run the Actor normally with a list of `audioUrls` to get one dataset row per file, containing the transcript, language, duration and full response. You can export it as CSV, Excel or JSON. Each file is billed at least 1 minute. For large batches of audio or video files with SRT/VTT output and a cheaper fast model, see the [media URL transcriber](https://apify.com/dropin-apis/media-url-transcriber). ```json { "audioUrls": ["https://upload.wikimedia.org/wikipedia/commons/d/dd/Armstrong_Small_Step.ogg"], "response_format": "srt" } ``` ### FAQ #### What is a whisper-1 alternative that still returns SRT and VTT? This Actor. `response_format=srt` or `vtt` works with the official OpenAI SDK after you change `base_url` and `api_key`. #### When is whisper-1 removed? 26 February 2027, per OpenAI's deprecations page: https://developers.openai.com/api/docs/deprecations #### Do I still get word-level timestamps? Yes. Send `timestamp_granularities[]=word` (and/or `segment`) with `response_format=verbose_json`, exactly as with whisper-1. #### How accurate is it compared with OpenAI whisper-1? It runs the open Whisper **small** model. We measured about 4% word error rate on clean English (LibriSpeech). Noisy audio, strong accents and rare languages do worse than OpenAI's larger model. #### How long can the audio be? Up to 10 minutes and 25 MB per request. Longer files are rejected with `400 audio_too_long`; split them first. #### What is the price? $0.0015 per started 15 seconds of audio, which is $0.006 per minute. A clip under 15 seconds costs $0.0015. Failed requests are not charged. #### Which languages are supported? All 99 Whisper languages, with auto-detection. Passing `language` (ISO-639-1) improves speed and accuracy. #### Do you keep my audio? No. Uploaded audio is decoded in memory, transcribed and discarded. Nothing is written to disk or logged. #### Is this affiliated with OpenAI? No. It is an independent service that implements the same public API shape and runs OpenAI's open-source Whisper model (MIT license) through faster-whisper. # Actor input Schema ## `audioUrls` (type: `array`): Public URLs of audio files (flac, m4a, mp3, mp4, mpeg, mpga, oga, ogg, wav, webm), up to 25 MB and 10 minutes each. ## `language` (type: `string`): ISO-639-1 code of the spoken language (e.g. en, es, de, ar). Leave empty to auto-detect. Ignored when translating. ## `response_format` (type: `string`): Format of the `response` field: json, text, srt, vtt or verbose\_json (segments with timestamps). ## `translate` (type: `boolean`): Translate the speech into English instead of transcribing it in the original language (like /v1/audio/translations). ## Actor input object example ```json { "audioUrls": [ "https://upload.wikimedia.org/wikipedia/commons/d/dd/Armstrong_Small_Step.ogg" ], "response_format": "verbose_json", "translate": false } ``` # Actor output Schema ## `results` (type: `string`): All items in the run's default dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "audioUrls": [ "https://upload.wikimedia.org/wikipedia/commons/d/dd/Armstrong_Small_Step.ogg" ] }; // Run the Actor and wait for it to finish const run = await client.actor("dropin-apis/whisper-compat").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "audioUrls": ["https://upload.wikimedia.org/wikipedia/commons/d/dd/Armstrong_Small_Step.ogg"] } # Run the Actor and wait for it to finish run = client.actor("dropin-apis/whisper-compat").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "audioUrls": [ "https://upload.wikimedia.org/wikipedia/commons/d/dd/Armstrong_Small_Step.ogg" ] }' | apify call dropin-apis/whisper-compat --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,dropin-apis/whisper-compat" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/55KZcNfdwj04FohL8/builds/LiZpvMEMejxYMaunz/openapi.json