GPT-4o Mini Transcribe overview
GPT-4o Mini Transcribe by OpenAI
Its advanced pretraining and reinforcement learning techniques make it ideal for real-time transcription in voice agents and call centers.
GPT-4o Mini Transcribe specs
- Model ID
openai/gpt-4o-mini-transcribe- Developer
- OpenAI
- Input
- Audio
- Output
- Text
- Endpoint
POST https://api.aimlapi.com/v1/stt/create
GPT-4o Mini-Transcribe API Overview
GPT-4o Mini Transcribe is a speech-to-text model from OpenAI designed to deliver highly accurate and efficient audio transcription. It represents a lighter, faster version of the full GPT-4o-Transcribe model, optimized for lower latency and resource consumption while maintaining excellent transcription quality. This model is ideal for developers seeking quick, reliable speech recognition in diverse and challenging acoustic environments.
Technical Specifications
- Model Type: Speech-to-text transcription model
- Architecture Basis: Built on GPT-4o-mini architecture, pretrained on specialized audio-centric datasets
- Token Context Window: Supports long audio inputs with up to 16,000 tokens context window
- Maximum Output Tokens: Up to 2,000 tokens per transcription output
- Training Data: Diverse, high-quality audio datasets including various accents, noise conditions, and speech speeds
- Training Techniques: Supervised fine-tuning and reinforcement learning to minimize word error rate and hallucinations
Performance Benchmarks
- Word Error Rate (WER): Significantly improved compared to earlier Whisper models and similar baselines
- Reliability: Performs robustly in noisy environments, with diverse accents, and varying speech speeds
- Language Recognition: Enhanced accuracy and language understanding capabilities across multiple languages
Key Features
- Efficiency: Lightweight model with fast inference times for quick transcription turnaround
- Robustness: Handles challenging audio with background noise, different accents, and speech variations
- Scalability: Can transcribe lengthy audio inputs without losing context due to the large token window
- Streaming Capability: Supports continuous audio streaming and transcription in real time
- Customizable Integration: Fits smoothly into voice agents, call centers, transcription services, and meeting applications
Comparison with Other Models
vs GPT-4o Transcribe: Mini Transcribe is better for low-latency applications, whereas the full Transcribe model suits accuracy-critical environments like legal or medical transcription.
vs OpenAI Whisper-Large: GPT-4o Mini Transcribe outperforms Whisper-Large in word error rate (WER) and streaming latency, thanks to reinforcement learning and specialized audio training. Whisper is more general-purpose but tends to be slower and less precise on noisy or accented speech.
vs Eleven Labs Scribe: While both models excel in streaming transcription, Eleven Labs Scribe reportedly matches or slightly exceeds GPT-4o-Mini-Transcribe in accuracy benchmarks in some third-party tests. GPT-4o-Mini speeds and integration with OpenAI’s ecosystem remain strong advantages.
Use cases
- Customer service call transcription and analytics
- Meeting and conference note-taking
- Voice assistant and voice agent transcription
- Legal and medical dictation transcription services
GPT-4o Mini Transcribe API pricing
| Usage | Price | Unit |
|---|---|---|
| Output | $5 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
How to use the GPT-4o Mini Transcribe API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/stt/create' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "openai/gpt-4o-mini-transcribe"
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "openai/gpt-4o-mini-transcribe"
}
response = requests.post("https://api.aimlapi.com/v1/stt/create", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/stt/create", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "openai/gpt-4o-mini-transcribe"
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());The request returns a generation id. Poll GET https://api.aimlapi.com/v1/stt/create?generation_id=<id> until the status is completed.
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GPT-4o Mini Transcribe FAQ
What inputs and outputs does GPT-4o Mini Transcribe support?
GPT-4o Mini Transcribe takes audio as input and returns text.
When was GPT-4o Mini Transcribe released?
GPT-4o Mini Transcribe became available on December 30, 2025.
How is GPT-4o Mini Transcribe billed?
GPT-4o Mini Transcribe is billed per generation, a fixed charge per output rather than by prompt length.
Who created GPT-4o Mini Transcribe?
GPT-4o Mini Transcribe was built by OpenAI.
How do I call GPT-4o Mini Transcribe on AI/ML API?
Send a request to v1 with openai/gpt-4o-mini-transcribe as the model id.
Is GPT-4o Mini Transcribe available through a single API key?
Yes. GPT-4o Mini Transcribe is served through AI/ML API, so the same key and endpoint format used for other models applies.
Is GPT-4o Mini Transcribe more accurate than Whisper?
Yes, OpenAI describes it as having improved accuracy compared to Whisper.
What is the context window and maximum output length for GPT-4o Mini Transcribe?
It has a 16,000 token context window and a maximum output of 2,000 tokens.
What is the GPT-4o Mini Transcribe model ID?
Use openai/gpt-4o-mini-transcribe as the model parameter. Requests go to https://api.aimlapi.com/v1/stt/create with your AI/ML API key.