Technical Specifications of `gpt-4o-mini-audio-preview`

Specification	Details
Model ID	`gpt-4o-mini-audio-preview`
Model Type	Compact multimodal audio-preview model
Core Modalities	Text input/output, speech input, speech output
Primary Interface Pattern	Chat-based interactions with multimodal message content
Audio Capabilities	Speech recognition, speech synthesis, mixed text-audio conversation
Streaming Support	Yes, suitable for real-time conversational flows
Tool / Function Calling	Supported for structured actions and workflow integration
Best For	Voice assistants, streaming transcription, IVR, call-bot workflows, in-app audio helpers
Interaction Style	Instruction-following conversational model with multimodal turns
Integration Pattern	API-based access through CometAPI using the `gpt-4o-mini-audio-preview` model ID

What is `gpt-4o-mini-audio-preview`?

gpt-4o-mini-audio-preview is a compact multimodal model designed for developers who want to build conversational audio experiences. It supports both speech input and speech output in addition to standard text interactions, making it well suited for applications where users talk naturally and expect spoken or text-based replies.

This model is especially useful when a product needs to combine automatic speech recognition, natural language understanding, and speech synthesis in a single conversational loop. Instead of treating transcription, reasoning, and response generation as separate components, gpt-4o-mini-audio-preview enables a unified workflow for mixed text-audio dialogs.

Because it also supports tool and function calling, the model can do more than just converse. It can trigger structured actions such as looking up account information, routing a customer support request, updating records, or invoking business logic inside a larger application. That makes it a strong fit for production voice systems such as virtual assistants, phone support agents, interactive voice response systems, transcription pipelines with summarization, and audio-enabled product assistants.

Main features of `gpt-4o-mini-audio-preview`

Speech input support: Accepts audio-driven user interactions so applications can process spoken requests naturally.
Speech output generation: Produces audio responses for assistants, call automation, and spoken guidance experiences.
Mixed text-audio conversations: Supports workflows where some turns are spoken and others are text-based, which is useful for hybrid interfaces.
Compact multimodal design: Offers audio-enabled capabilities in a lighter-weight model footprint appropriate for responsive applications.
Streaming responses: Helps power low-latency, real-time experiences such as live assistants and streaming transcription systems.
Tool/function calling: Enables the model to invoke structured tools or business functions for tasks beyond open-ended conversation.
Instruction following: Follows application-level guidance to keep responses aligned with product behavior and workflow requirements.
Transcription and summarization workflows: Useful for turning spoken interactions into structured text outputs, summaries, or downstream actions.
IVR and call-bot readiness: Fits customer support and telephony scenarios where spoken interaction and task routing are central.
In-app audio assistance: Can be embedded into software products that need voice-enabled help, onboarding, or guided actions.

How to access and integrate `gpt-4o-mini-audio-preview`

To start using gpt-4o-mini-audio-preview, first create an account on CometAPI and generate your API key from the dashboard. This key is used to authenticate every request and connect your application securely to the model.

Step 2: Send Requests to `gpt-4o-mini-audio-preview` API

Use CometAPI's OpenAI-compatible endpoint with audio input/output support.

curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_API_KEY" \
  -d '{
    "model": "gpt-4o-mini-audio-preview",
    "modalities": ["text", "audio"],
    "audio": {
      "voice": "alloy",
      "format": "wav"
    },
    "messages": [
      {
        "role": "user",
        "content": "Tell me a short joke."
      }
    ]
  }'

Step 3: Retrieve and Verify Results