openai/wizper
Wizper by OpenAI - accurate speech-to-text transcription with AI. Convert audio and video to text with high accuracy, multilingual support, and speaker identification.
Example output — click Run to generate your own
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OpenAI-compatible endpoint with unified authentication and usage tracking.
https://api.sandbase.ai/v1/runopenai/wizperInput Schema
7 parameters · 0 required · 7 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
task | string | Optional | Task to perform on the audio file. Either transcribe or translate. · Options: transcribe, translate · Default: "transcribe" transcribetranslate |
audio | string | Optional | URL of the audio file to transcribe. Supported formats: mp3, mp4, mpeg, mpga, m4a, wav or webm. |
version | string | Optional | Version of the model to use. All of the models are the Whisper large variant. · Default: "3" |
language | string | Optional |
Language of the audio file.
If translate is selected as the task, the audio will be translated to
English, regardless of the language selected. If `None` is passed,
the language will be automatically detected. This will also increase
the inference time.
· Options: af, am, ar, as, az, ba, be, bg, bn, bo, br, bs, ca, cs, cy, da, de, el, en, es, et, eu, fa, fi, fo, fr, gl, gu, ha, haw, he, hi, hr, ht, hu, hy, id, is, it, ja, jw, ka, kk, km, kn, ko, la, lb, ln, lo, lt, lv, mg, mi, mk, ml, mn, mr, ms, mt, my, ne, nl, nn, no, oc, pa, pl, ps, pt, ro, ru, sa, sd, si, sk, sl, sn, so, sq, sr, su, sv, sw, ta, te, tg, th, tk, tl, tr, tt, uk, ur, uz, vi, yi, yo, zh · Default: "en" afamarasazbabebgbnbobrbscacscydadeeleneseteufafifofrglguhahawhehihrhthuhyidisitjajwkakkkmknkolalblnloltlvmgmimkmlmnmrmsmtmynenlnnnoocpaplpsptrorusasdsiskslsnsosqsrsusvswtatetgthtktltrttukuruzviyiyozh |
chunk_level | string | Optional | Level of the chunks to return. · Default: "segment" |
merge_chunks | boolean | Optional | Whether to merge consecutive chunks. When enabled, chunks are merged if their combined duration does not exceed max_segment_len. · Default: true |
max_segment_len | integer | Optional | Maximum speech segment duration in seconds before splitting. · Min: 10 · Max: 29 · Default: 29 |
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
Async Workflow
This model uses asynchronous execution. Submit a request and poll for the result.
- Submit — POST to /v1/run, receive an
id - Poll — GET /v1/run/{id} until status is
completed,failed, ortimeout - Retrieve — Read
outputsfrom the completed response
Code Examples
Ready-to-run snippets
# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "openai/wizper",
"task": "transcribe",
"audio": "https://static.sandbase.ai/examples/elevenlabs/scribe-v2/input_audio_0.mp3",
"version": "3",
"language": "en",
"chunk_level": "segment",
"merge_chunks": true,
"max_segment_len": 29,
"prompt": "a beautiful sunset over mountains"
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
Wizper
Wizper is the Wizper route for transcription, turning spoken audio or video into a production-ready result while keeping the operation distinct from neighboring endpoints. Wizper by OpenAI - accurate speech-to-text transcription with AI. Convert audio and video to text with high accuracy, multilingual support, and speaker identification. The workflow is designed for creators who need the model’s specific transformation to remain visible in the request, so the source, intended change, and finished artifact can be reviewed as one coherent creative decision.
In practical use, this route exposes task, version, language, audio_url, sync_mode, chunk_level, merge_chunks, max_segment_len to shape the exact deliverable. Those controls let a team preserve the important source constraints, state subject behavior or material treatment precisely, choose supported timing or output characteristics, and reproduce successful settings across alternate takes. The result fits an iterative pipeline: establish the core brief, compare controlled variations, then pass the selected asset into editorial, design, localization, visualization, or publishing work.
Highlights
- Transcribe or translate. Turn supported audio or video into source-language text, or translate the spoken content into English.
- Broad language coverage. Choose from the documented language codes while retaining explicit control over the recognition task.
- Segment-aware processing. Tune chunk level, maximum segment length, and consecutive-chunk merging for long recordings.
- Media-ready ingestion. Accept common MP3, MP4, MPEG, MPGA, M4A, WAV, and WebM assets through one transcription route.
Pricing
| Configuration | Price |
|---|---|
| Per request | $0.006000 |
When to Use
| Scenario | Why it fits |
|---|---|
| Exact workflow fit | Choose this route when the required deliverable is transcription, rather than a related route with different source media. |
| Directed creative iteration | Use it when subject, motion, material, speech, framing, or finish should be expressed explicitly and compared across controlled variants. |
| Existing-asset continuity | Use it when supplied images, video, audio, references, or styles must remain the anchor for the generated result. |
| Repeatable production | Use it when successful inputs need to be saved and rerun across a campaign, asset set, localization pass, or batch. |
| Pipeline handoff | Use it when the returned artifact will move into editorial, compositing, visualization, review, storage, or publishing. |
Prompt Guide
Start with the source or subject, then describe the intended transformation, movement or behavior, camera and composition, and the desired finish. Keep media URLs reachable, use only fields documented for this exact route, and change one major control at a time when comparing results. For source-led tasks, describe what should change as well as what must remain recognizable.
{}
Technical Specs
| Property | Value |
|---|---|
| Model ID | openai/wizper |
| Execution mode | async |
| Required inputs | None marked required |
task | string; options: transcribe, translate; default: transcribe |
version | string; default: 3 |
language | string; default: en |
audio_url | string |
sync_mode | boolean; default: false |
chunk_level | string; default: segment |
merge_chunks | boolean; default: true |
max_segment_len | integer; minimum: 10; maximum: 29; default: 29 |
Related Models
openai/gpt-image-1openai/gpt-image-1-miniopenai/gpt-image-1.5openai/gpt-image-2