OpenAI GPT Transcribe — OpenAI's current file-transcription model and the successor to GPT-4o Transcribe and Whisper. Detects the spoken language automatically and accepts custom vocabulary. Returns the transcript text without word-level timestamps.
62 languages · benchmarked
GPT Transcribe is a speech-to-text model from OpenAI. In our standardized benchmarks it reaches 9.58% word error rate, ranking #4 of 36 models tested. It supports 62 languages and runs at $0.005/min — cheaper than most alternatives.
Its nearest benchmarked alternative is MAI-Transcribe-2 (preview). Best suited for multilingual workloads, accuracy-critical work, and high-volume, cost-sensitive pipelines.
Overall Score
79.2
#4 of 36
Word Error Rate
9.58%
Character Error Rate
7.11%
Match Error Rate
9.24%
Word Info Lost
13.69%
Avg Latency
2.3s
Benchmarks Run
35
overall WER · 36 models
GPT Transcribe
field · 35 models
lower-left is better
8 categories
WER
lower is better
Medical
2.3%
Legal
3.1%
Technical
4.2%
Finance
5.6%
General
8.3%
Conversational
11.4%
Code-Switching
20.4%
Noisy Environment
20.8%
| Category | WER | CER | MER | WIL | Latency | Benchmarks |
|---|---|---|---|---|---|---|
Code-Switching | 20.40% | 14.84% | 19.95% | 25.65% | 3.8s | 2 |
Conversational | 11.43% | 7.04% | 11.40% | 14.56% | 3.2s | 2 |
Finance | 5.63% | 2.87% | 5.56% | 8.46% | 2.8s | 2 |
General | 8.31% | 6.45% | 8.17% | 12.99% | 2.1s | 19 |
Legal | 3.07% | 1.90% | 3.06% | 4.44% | 3.4s | 2 |
Medical | 2.26% | 1.27% | 2.26% | 3.21% | 2.3s | 2 |
Noisy Environment | 20.83% | 16.44% | 18.81% | 27.49% | 1.4s | 4 |
Technical | 4.22% | 2.44% | 4.21% | 4.90% | 2.9s | 2 |
5 accents
| Accent | WER | Benchmarks |
|---|---|---|
African | 18.46% | 1 |
Australian | 23.08% | 1 |
Indian | 20.63% | 1 |
British | 11.94% | 1 |
American | 11.32% | 1 |
Rate
$0.0045
/min
Per-second billing. Bring your own provider key and pay your provider directly — a 5% routing fee applies (first 100 min/mo free).
Set up BYOKCost estimator
1 hour
$0.27
10 hours
$2.70
100 hours
$27
1,000 hours
$270
Billed per second of audio processed.
Model ID
openai/gpt-transcribe
Authenticate every request with your secret API key as a Bearer token. Issue a key from your dashboard.
Use it with your agent
Paste this into Claude Code, Cursor, Codex or any agent with a shell. It installs the CLI and the OpenTranscription skill, then transcribes with this model.
Quickstart
Upload your audio, create a job with this model, then poll the job or set a webhook_url to be notified when it completes.
Key parameters
file_path
string
required
Storage path returned by the upload step.
model
string
required
The model to run this job on.
models
string[]
Ordered fallback chain: primary first, then backups tried in order if a provider fails.
language
string
ISO 639-1 language code. Omit to auto-detect.
word_timestamps
boolean
Per-word start, end and confidence. Defaults to true; send false to leave them out.
custom_words
string[]
Names, jargon and product terms to bias the model toward. Up to 1000 entries.
vocabulary_list_id
uuid
A vocabulary list saved in your workspace. Merged with custom_words when both are sent.
webhook_url
string
HTTPS URL notified with the result when the job completes. Delivered events are signed (X-OT-Signature).
title
string
Display name for this job in the dashboard. Falls back to the file name.
Response
A completed job returns the transcript in the OpenTranscription Unified Schema (OTUS).
Webhooks — skip polling
We POST a signed event to your webhook_url when a job completes or fails; verify the X-OT-Signature (HMAC-SHA256, reject if older than 300 s) and dedupe on the event id, then fetch the full transcript via GET /api/v1/transcriptions/{id}.
Rate-limited per tier — see the X-RateLimit-* response headers.
Full API referencefrom the same field
same benchmark, every match
Supported Languages
Supported Formats
Features
Limits
Max file size
25 MB
Max duration
No documented limit