Overall Score
81.1
Word Error Rate
13.58%
Character Error Rate
9.32%
Match Error Rate
12.84%
Word Info Lost
17.77%
Avg Latency
2.0s
Benchmarks Run
35
last 30 runs
Word error rate
16.38%
↓ 19.4% · 30d
3 runs ago
latest
Avg latency
2.4s
↑ 24.4% · 30d
3 runs ago
latest
overall WER · 28 models
field · 28 models
lower-left is better
8 categories
WER
lower is better
Medical
3.5%
Technical
4.0%
Legal
4.9%
Finance
6.0%
General
11.2%
Conversational
12.4%
Code-Switching
18.6%
Noisy Environment
40.8%
5 accents
pay per second
Rate
$0.003
/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
$0.18
10 hours
$1.80
100 hours
$18
1,000 hours
$180
Billed per second of audio processed.
POST /api/v1/transcriptions
Model ID
openai/gpt-4o-mini-transcribe
Authenticate every request with your secret API key as a Bearer token. Issue a key from your dashboard.
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.
language
string
ISO 639-1 language code. Omit to auto-detect.
webhook_url
string
HTTPS URL notified with the result when the job completes. Delivered events are signed (X-OT-Signature).
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 referenceSupported Languages
Supported Formats
Features
GPT-4o Mini Transcribe is a speech-to-text model from OpenAI. It supports 98 languages and runs at $0.003/min — cheaper than most alternatives.
Its nearest benchmarked alternative is Amazon Transcribe. Best suited for multilingual workloads and high-volume, cost-sensitive pipelines.