What industries can use GPT-Realtime-2.1 API?

GPT-Realtime-2.1 is suitable for customer service, sales automation, healthcare assistants, education platforms, and smart device applications.

How large is the GPT-Realtime-2.1 context window?

GPT-Realtime-2.1 supports a 128,000 token context window and up to 32,000 output tokens.

Can GPT-Realtime-2.1 API create real-time voice assistants?

Yes. GPT-Realtime-2.1 is designed for speech-to-speech applications and enables developers to build low-latency conversational voice agents.

What input and output modalities does GPT-Realtime-2.1 support?

GPT-Realtime-2.1 supports text and audio input/output plus image input, but it does not support video input.

What improvements does GPT-Realtime-2.1 have over GPT-Realtime-2?

GPT-Realtime-2.1 improves alphanumeric recognition, silence handling, noise robustness, and interruption behavior while maintaining realtime reasoning and tool-use capabilities.

When should developers choose GPT-Realtime-2.1 instead of GPT-4o Realtime API?

Developers should choose GPT-Realtime-2.1 for advanced voice agents requiring stronger reasoning, tool execution, and complex conversational workflows.

OpenAI

Available

gpt-realtime-2.1

GPT-Realtime-2.1 API

Q: Does GPT-Realtime-2.1 support function calling?

Yes. GPT-Realtime-2.1 supports tool use and function calling, allowing voice agents to execute external actions during conversations.

GPT-Realtime-2.1 updates GPT-Realtime-2 with improved alphanumeric recognition, silence and noise handling, and interruption behavior. It supports speech-to-speech interactions with configurable reasoning effort, instruction following, and tool use for complex voice-agent workflows.

Starting price

$3.20 / 1M input tokens

Usage-based billing

API health

Available

Production endpoint

Response

Async ready

Observed API response

Released

Aug 7, 2026

OpenAI

Pricing

Use the quick estimate above for a single run, then review the full CometAPI and official-price comparison.

First request

$0.0224

Estimated CometAPI usage cost

Ten requests

$0.2240

Estimated CometAPI usage cost

Fifteen requests

$0.3360

Estimated CometAPI usage cost

⇌

Credits conversion

1,000 credits = $1

Credits make budgets comparable across token, request and runtime billing. The USD amount remains the source of truth at checkout.

✓Current model in credits

Input

3,200

credits / 1M tokens

Output

19,200

credits / 1M tokens

Minimum charge transparency This prototype does not assume a hidden per-request minimum. If a production billing floor or minimum top-up applies, it must be displayed before purchase and included in every budget estimate.

Model	Comet Price (USD / M Tokens)	Official Price (USD / M Tokens)	Discount
gpt-realtime-2.1	Input: $3.20/M Output: $19.20/M	Input: $4.00/M Output: $24.00/M	-20%
gpt-realtime-2.1-mini	Input: $0.4800/M Output: $2.88/M	Input: $0.6000/M Output: $3.60/M	-20%

Model brief

A stable model identity for search and evaluation, paired with live catalog data that can change without rewriting the page's core SEO structure.

Stable identity

What is GPT-Realtime-2.1?

Canonical model identity stays stable as pricing and limits change.

Live model data

Current catalog snapshot

Availability

Available

Starting price

$3.20 / 1M input tokens

Context

See capabilities

Catalog date

Aug 7, 2026

Overview

A practical overview of GPT-Realtime-2.1, including important behavior and integration considerations.

Technical Specifications of GPT-Realtime-2.1

Specification	Details
Model name	GPT-Realtime-2.1
Provider	OpenAI
Model family	GPT-Realtime series
Model type	Real-time multimodal voice reasoning model
Primary capability	Speech-to-speech AI agents
Input modalities	Text, Audio, Image
Output modalities	Text, Audio
Context window	128,000 tokens
Maximum output tokens	32,000 tokens
Reasoning support	Configurable reasoning effort
Function calling	Supported
Structured outputs	Not supported
Fine-tuning	Not supported
Video input	Not supported
Main API endpoint	Realtime API
Knowledge cutoff	September 30, 2024

Source: OpenAI GPT-Realtime-2.1 model documentation.

What is GPT-Realtime-2.1?

GPT-Realtime-2.1 is OpenAI's advanced real-time voice model designed for building conversational AI agents that can listen, reason, and respond naturally through audio.

Compared with traditional voice assistants that rely on separate speech recognition, language understanding, and text-to-speech pipelines, GPT-Realtime-2.1 provides native speech-to-speech interaction, enabling lower-latency conversations with better interruption handling and contextual understanding.

The model is optimized for production voice applications including customer service agents, AI assistants, sales automation, education platforms, and interactive voice experiences.

GPT-Realtime-2.1 Benchmark Performance

GPT-Realtime-2.1 improvements focus on practical realtime interaction metrics:

Capability	Improvement
Voice interruption handling	Improved
Noise robustness	Improved
Alphanumeric recognition	Improved
Tool-based voice workflows	Supported
Speech-to-speech interaction	Supported

Main Features of GPT-Realtime-2.1

1. Native Speech-to-Speech Interaction

GPT-Realtime-2.1 removes the need for separate speech recognition and text-to-speech pipelines.

Traditional voice architecture:

User Voice
 ↓
Speech-to-Text
 ↓
LLM Processing
 ↓
Text-to-Speech
 ↓
Voice Response

GPT-Realtime-2.1:

User Voice
 ↓
GPT-Realtime-2.1
 ↓
Voice Response

This reduces latency and improves conversational flow.

2. Improved Voice Conversation Quality

GPT-Realtime-2.1 improves several real-world voice challenges:

Better interruption handling

Users can interrupt the AI naturally while it is speaking.

Example:

User:

"Book me a flight to—actually change that to Tokyo."

The model can recover from conversational changes without restarting the interaction.

Better silence and noise handling

The model is optimized for environments where audio quality is imperfect:

Call centers
Mobile devices
Public spaces
Smart devices

3. Advanced Voice Agent Tool Use

GPT-Realtime-2.1 supports tool calling, allowing voice agents to perform actions.

Examples:

Customer service:

User:
"Where is my order?"

AI:
→ Calls order database API
→ Retrieves status
→ Responds by voice

Enterprise workflow:

Voice command
↓
Reasoning
↓
API execution
↓
Voice confirmation

This makes GPT-Realtime-2.1 suitable for autonomous voice agents.

4. Configurable Reasoning Capability

Unlike earlier realtime voice models optimized primarily for speed, GPT-Realtime-2.1 introduces configurable reasoning effort.

Developers can balance:

Response latency
Accuracy
Task complexity

Low reasoning:

Simple conversations
FAQ assistants

Higher reasoning:

Complex customer requests
Multi-step workflows
Business operations

5. Better Recognition of Numbers and Technical Information

Voice agents often struggle with:

Account numbers
Serial numbers
Addresses
Product codes
Financial information

GPT-Realtime-2.1 improves alphanumeric recognition, making it more suitable for enterprise voice systems.

6. Multimodal Input Support

GPT-Realtime-2.1 supports:

Input	Support
Text	✅
Audio	✅
Image	✅
Video	❌

Image input enables scenarios such as:

Visual customer support
Document interpretation
Camera-based assistants

GPT-Realtime-2.1 vs GPT-Realtime-2 vs GPT-4o Realtime

Model	Strength	Best Use
GPT-Realtime-2.1	Best realtime reasoning + voice agent capability	Production voice agents
GPT-Realtime-2	Strong realtime voice reasoning	Advanced conversational apps
GPT-4o Realtime	Fast multimodal interaction	General voice assistants

GPT-Realtime-2.1 vs GPT-Realtime-2

GPT-Realtime-2.1 improves:

Voice interruption recovery
Noise handling
Recognition accuracy
Conversational robustness

Both models share:

Speech-to-speech architecture
Tool calling
Reasoning support
Realtime API access

GPT-Realtime-2.1 vs GPT-4o Realtime

GPT-Realtime-2.1 is positioned for more advanced agent workflows.

Compared with GPT-4o Realtime:

Capability	GPT-Realtime-2.1	GPT-4o Realtime
Reasoning	Stronger	General
Context	128K	32K
Tool use	Supported	Supported
Voice agents	Advanced	General
Complex workflows	Better suited	Suitable

How to Use GPT-Realtime-2.1 API with CometAPI

GPT-Realtime-2.1 is designed for low-latency voice agent applications. It supports real-time speech-to-speech interaction, audio input/output, image input, configurable reasoning effort, and function calling for tool-enabled voice workflows. OpenAI exposes it through the Realtime API, including WebRTC, WebSocket, and SIP-based real-time communication methods.

CometAPI provides a unified API layer for integrating advanced AI models, allowing developers to access GPT-Realtime-2.1-style workflows without maintaining separate provider authentication, SDK logic, and infrastructure.

Step 1: Get Your CometAPI API Key

Create a CometAPI account and generate an API token from the developer console.

Your API request should include:

Authorization: Bearer YOUR_COMETAPI_API_KEY
Content-Type: application/json

The API key authenticates your requests and allows your application to call available AI models through CometAPI.

Step 2: Create a GPT-Realtime-2.1 Session

GPT-Realtime-2.1 works through a persistent realtime session instead of traditional request-response chat completion.

A realtime session maintains:

Audio input stream
Model responses
Conversation state
Tool calls
Interruptions

OpenAI's Realtime API supports real-time communication through WebRTC, WebSocket, and SIP interfaces.

Example:

curl https://api.cometapi.com/v1/realtime/sessions \
-H "Authorization: Bearer YOUR_COMETAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '
{
  "model": "gpt-realtime-2.1",
  "modalities": [
    "audio",
    "text"
  ],
  "voice": "alloy",
  "instructions": "You are a helpful customer support voice assistant."
}
'

Example response:

{
  "id": "sess_xxxxx",
  "model": "gpt-realtime-2.1",
  "status": "active"
}

Step 3: Send Audio Input to GPT-Realtime-2.1

After creating a session, stream user audio.

Example workflow:

User microphone
        |
        ↓
Audio stream
        |
        ↓
GPT-Realtime-2.1
        |
        ↓
Generated voice response

Audio input can include:

Phone conversations
Voice commands
Customer support calls
Interactive assistants

GPT-Realtime-2.1 improves speech interaction with better silence detection, noise handling, and interruption behavior compared with earlier realtime models.

Step 4: Receive Real-Time Audio Responses

The model returns generated audio responses through the realtime connection.

Example event:

{
  "type": "response.audio.delta",
  "delta": "base64_audio_chunk"
}

Your application can immediately play received audio chunks.

Typical implementations:

WebRTC voice applications
Browser-based assistants
Mobile voice apps
AI phone agents

Step 5: Add Function Calling for Voice Agents

GPT-Realtime-2.1 supports function calling, allowing voice agents to execute external actions.

Example:

{
  "tools": [
    {
      "type": "function",
      "name": "check_order_status",
      "description": "Retrieve customer order information",
      "parameters": {
        "type": "object",
        "properties": {
          "order_id": {
            "type": "string"
          }
        }
      }
    }
  ]
}

Possible voice-agent workflows:

"Where is my package?"
"Book me a meeting tomorrow."
"Cancel my subscription."
"Check my account balance."

The model can recognize the request, call the appropriate tool, and continue the conversation naturally.

Step 6: Configure Reasoning and Instructions

GPT-Realtime-2.1 supports configurable reasoning effort.

Example:

{
  "model": "gpt-realtime-2.1",
  "reasoning": {
    "effort": "medium"
  },
  "instructions": "Act as a professional travel assistant."
}

Recommended settings:

Application	Reasoning Level
Simple voice commands	Low
Customer support	Medium
Complex workflow agents	High

FAQ

API

Copy a working endpoint and code example, then open the complete API reference when you need every parameter.

One API, production-ready model access

Authenticate once, call the model endpoint and keep the same billing and observability workflow across providers.

GET/v1/realtime

Sample code and API for GPT-Realtime-2.1

Access comprehensive sample code and API resources for GPT-Realtime-2.1 to streamline your integration process. Our detailed documentation provides step-by-step guidance, helping you leverage the full potential of GPT-Realtime-2.1 in your projects.

GET

/v1/realtime

set -euo pipefail

# curl can perform the HTTP Upgrade handshake and print the Realtime WebSocket
# byte stream. Use the Python or JavaScript example to send framed events.
WEBSOCKET_KEY="$(openssl rand -base64 16)"

curl --http1.1 --include --no-buffer \
  --request GET \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "OpenAI-Beta: realtime=v1" \
  --header "Connection: Upgrade" \
  --header "Upgrade: websocket" \
  --header "Sec-WebSocket-Version: 13" \
  --header "Sec-WebSocket-Key: ${WEBSOCKET_KEY}" \
  "https://api.cometapi.com/v1/realtime""?model=gpt-realtime-2.1"

cURL Code Example

set -euo pipefail

# curl can perform the HTTP Upgrade handshake and print the Realtime WebSocket
# byte stream. Use the Python or JavaScript example to send framed events.
WEBSOCKET_KEY="$(openssl rand -base64 16)"

curl --http1.1 --include --no-buffer \
  --request GET \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "OpenAI-Beta: realtime=v1" \
  --header "Connection: Upgrade" \
  --header "Upgrade: websocket" \
  --header "Sec-WebSocket-Version: 13" \
  --header "Sec-WebSocket-Key: ${WEBSOCKET_KEY}" \
  "https://api.cometapi.com/v1/realtime""?model=gpt-realtime-2.1"

Python Code Example

"""Send one text turn to gpt-realtime-2.1 over the Realtime WebSocket API.

Install the client with: pip install websocket-client
"""

import json
import os
from urllib.parse import urlencode

from websocket import create_connection


MODEL = "gpt-realtime-2.1"
BASE_URL = "wss://api.cometapi.com"
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"


def get(path: str) -> str:
    """Build a WebSocket URL for the API's GET route."""

    return f"{BASE_URL}{path}?{urlencode({'model': MODEL})}"


socket = create_connection(
    get("/v1/realtime"),
    header=[
        f"Authorization: Bearer {COMETAPI_KEY}",
        "OpenAI-Beta: realtime=v1",
    ],
    timeout=30,
)

try:
    socket.send(
        json.dumps(
            {
                "type": "session.update",
                "session": {
                    "modalities": ["text"],
                    "instructions": "Answer clearly and concisely.",
                },
            }
        )
    )
    socket.send(
        json.dumps(
            {
                "type": "conversation.item.create",
                "item": {
                    "type": "message",
                    "role": "user",
                    "content": [
                        {
                            "type": "input_text",
                            "text": "Give me one tip for a productive meeting.",
                        }
                    ],
                },
            }
        )
    )
    socket.send(json.dumps({"type": "response.create"}))

    while True:
        event = json.loads(socket.recv())
        event_type = event.get("type")
        if event_type in {
            "response.text.delta",
            "response.output_text.delta",
            "response.audio_transcript.delta",
            "response.output_audio_transcript.delta",
        }:
            print(event.get("delta", ""), end="", flush=True)
        elif event_type == "error":
            raise RuntimeError(json.dumps(event.get("error", event), indent=2))
        elif event_type == "response.done":
            print()
            break
finally:
    socket.close()

JavaScript Code Example

// Send one text turn to gpt-realtime-2.1 over the Realtime WebSocket API.
// Requires Node.js 22 or newer, which includes a global WebSocket client.

const model = "gpt-realtime-2.1";
const baseUrl = "wss://api.cometapi.com";
const apiKey = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";

function get(path) {
  const url = new URL(`${baseUrl}${path}`);
  url.searchParams.set("model", model);
  return url;
}

const socket = new WebSocket(get("/v1/realtime"), [
  "realtime",
  `openai-insecure-api-key.${apiKey}`,
  "openai-beta.realtime-v1",
]);

socket.addEventListener("open", () => {
  socket.send(
    JSON.stringify({
      type: "session.update",
      session: {
        modalities: ["text"],
        instructions: "Answer clearly and concisely.",
      },
    }),
  );
  socket.send(
    JSON.stringify({
      type: "conversation.item.create",
      item: {
        type: "message",
        role: "user",
        content: [
          {
            type: "input_text",
            text: "Give me one tip for a productive meeting.",
          },
        ],
      },
    }),
  );
  socket.send(JSON.stringify({ type: "response.create" }));
});

socket.addEventListener("message", ({ data }) => {
  const event = JSON.parse(data.toString());
  if (
    [
      "response.text.delta",
      "response.output_text.delta",
      "response.audio_transcript.delta",
      "response.output_audio_transcript.delta",
    ].includes(event.type)
  ) {
    process.stdout.write(event.delta || "");
  } else if (event.type === "error") {
    console.error(JSON.stringify(event.error || event, null, 2));
    socket.close();
    process.exitCode = 1;
  } else if (event.type === "response.done") {
    process.stdout.write("\n");
    socket.close();
  }
});

socket.addEventListener("error", (error) => {
  console.error("WebSocket error:", error.message || error);
  process.exitCode = 1;
});

Capabilities

Scan the model facts that matter before you choose an architecture or estimate production workload.

Supported capabilities

Features returned by the existing model API.

text-to-speech

Input and output

Inputs

text

Outputs

audio

Production profile

Provider: OpenAI
Context: Model specific
Commercial use: Supported

Use cases

Use GPT-Realtime-2.1 for production workflows that match its audio capabilities, then compare alternatives before committing to a long-term integration.

Speech, music and audio generation

Voice experiences and media production

Automated audio workflows at scale

Other models

Compare other models available through CometAPI for different quality, latency, capability and pricing trade-offs.

Open model comparison →

ElevenLabs

Eleven V4

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ElevenLabs Voice Dubbing

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ElevenLabs

ElevenLabs Voice Isolation

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Bytedance

Seed Audio

Explore the Seed Audio API.

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OpenAI

GPT-4o mini Audio

GPT-4o mini Audio is a multimodal model for speech and text interactions. It performs speech recognition, translation, and text-to-speech, follows instructions, and can call tools for structured actions with streaming responses. Typical uses include real-time voice assistants, live captioning and translation, call summarization, and voice-controlled applications. Technical highlights include audio input and output, streaming responses, function calling, and structured JSON output.

View model

OpenAI

GPT-4o Transcribe

GPT-4o Transcribe is an audio-to-text model for multilingual, low-latency speech recognition. It supports real-time streaming and batch transcription from common audio formats with punctuation and sentence segmentation. Typical uses include live captions, voice assistant input, meeting notes, and media or call recording transcription. Technical highlights include audio modality support, long-form processing, and APIs suited for interactive and server-side workflows.

View model

Uptime

Review live heartbeat data, endpoint availability and observed response times before moving into production.

Uptime

Request success rate over the last 30 days, reflecting the reliability of each model provider. CometAPI monitors all connected providers in real time, 24/7.

Respond

2010msAvg. Response

Uptime

70.2%Avg. Uptime

Versions

Review available model identifiers before pinning a production integration.

gpt-realtime-2.1

gpt-realtime-2.1-mini

Updates

Follow meaningful availability, pricing and capability changes for GPT-Realtime-2.1 without losing the stable model page.

Model changelog

One page that gets stronger over time.

Release notes, pricing changes, benchmark updates and migration guidance accumulate here while the canonical URL stays unchanged.

Aug 7, 2026

API availability confirmed

GPT-Realtime-2.1 is available through the CometAPI model catalog and API documentation.

Current

Live data

Pricing and limits synced from the catalog

Price, context, availability and limits are treated as dynamic properties instead of being embedded in the page title or model identity.

Aug 7, 2026

Permanent model entity created

The provider and model slug form a durable canonical URL; future content and data updates remain on this page.

Keep exploring

Compare models and continue your research

OpenAI

Available

gpt-realtime-2.1

GPT-Realtime-2.1 API

Starting price

$3.20 / 1M input tokens

Usage-based billing

API health

Available

Production endpoint

Response

Async ready

Observed API response

Released

Aug 7, 2026

OpenAI

Pricing

Use the quick estimate above for a single run, then review the full CometAPI and official-price comparison.

First request

$0.0224

Estimated CometAPI usage cost

Ten requests

$0.2240

Estimated CometAPI usage cost

Fifteen requests

$0.3360

Estimated CometAPI usage cost

⇌

Credits conversion

1,000 credits = $1

Credits make budgets comparable across token, request and runtime billing. The USD amount remains the source of truth at checkout.

✓Current model in credits

Input

3,200

credits / 1M tokens

Output

19,200

credits / 1M tokens

Model	Comet Price (USD / M Tokens)	Official Price (USD / M Tokens)	Discount
gpt-realtime-2.1	Input: $3.20/M Output: $19.20/M	Input: $4.00/M Output: $24.00/M	-20%
gpt-realtime-2.1-mini	Input: $0.4800/M Output: $2.88/M	Input: $0.6000/M Output: $3.60/M	-20%

Model brief

A stable model identity for search and evaluation, paired with live catalog data that can change without rewriting the page's core SEO structure.

Stable identity

What is GPT-Realtime-2.1?

Canonical model identity stays stable as pricing and limits change.

Live model data

Current catalog snapshot

Availability

Available

Starting price

$3.20 / 1M input tokens

Context

See capabilities

Catalog date

Aug 7, 2026

Overview

A practical overview of GPT-Realtime-2.1, including important behavior and integration considerations.

Technical Specifications of GPT-Realtime-2.1

Specification	Details
Model name	GPT-Realtime-2.1
Provider	OpenAI
Model family	GPT-Realtime series
Model type	Real-time multimodal voice reasoning model
Primary capability	Speech-to-speech AI agents
Input modalities	Text, Audio, Image
Output modalities	Text, Audio
Context window	128,000 tokens
Maximum output tokens	32,000 tokens
Reasoning support	Configurable reasoning effort
Function calling	Supported
Structured outputs	Not supported
Fine-tuning	Not supported
Video input	Not supported
Main API endpoint	Realtime API
Knowledge cutoff	September 30, 2024

Source: OpenAI GPT-Realtime-2.1 model documentation.

What is GPT-Realtime-2.1?

GPT-Realtime-2.1 is OpenAI's advanced real-time voice model designed for building conversational AI agents that can listen, reason, and respond naturally through audio.

The model is optimized for production voice applications including customer service agents, AI assistants, sales automation, education platforms, and interactive voice experiences.

GPT-Realtime-2.1 Benchmark Performance

GPT-Realtime-2.1 improvements focus on practical realtime interaction metrics:

Capability	Improvement
Voice interruption handling	Improved
Noise robustness	Improved
Alphanumeric recognition	Improved
Tool-based voice workflows	Supported
Speech-to-speech interaction	Supported

Main Features of GPT-Realtime-2.1

1. Native Speech-to-Speech Interaction

GPT-Realtime-2.1 removes the need for separate speech recognition and text-to-speech pipelines.

Traditional voice architecture:

User Voice
 ↓
Speech-to-Text
 ↓
LLM Processing
 ↓
Text-to-Speech
 ↓
Voice Response

GPT-Realtime-2.1:

User Voice
 ↓
GPT-Realtime-2.1
 ↓
Voice Response

This reduces latency and improves conversational flow.

2. Improved Voice Conversation Quality

GPT-Realtime-2.1 improves several real-world voice challenges:

Better interruption handling

Users can interrupt the AI naturally while it is speaking.

Example:

User:

"Book me a flight to—actually change that to Tokyo."

The model can recover from conversational changes without restarting the interaction.

Better silence and noise handling

The model is optimized for environments where audio quality is imperfect:

Call centers
Mobile devices
Public spaces
Smart devices

3. Advanced Voice Agent Tool Use

GPT-Realtime-2.1 supports tool calling, allowing voice agents to perform actions.

Examples:

Customer service:

User:
"Where is my order?"

AI:
→ Calls order database API
→ Retrieves status
→ Responds by voice

Enterprise workflow:

Voice command
↓
Reasoning
↓
API execution
↓
Voice confirmation

This makes GPT-Realtime-2.1 suitable for autonomous voice agents.

4. Configurable Reasoning Capability

Unlike earlier realtime voice models optimized primarily for speed, GPT-Realtime-2.1 introduces configurable reasoning effort.

Developers can balance:

Response latency
Accuracy
Task complexity

Low reasoning:

Simple conversations
FAQ assistants

Higher reasoning:

Complex customer requests
Multi-step workflows
Business operations

5. Better Recognition of Numbers and Technical Information

Voice agents often struggle with:

Account numbers
Serial numbers
Addresses
Product codes
Financial information

GPT-Realtime-2.1 improves alphanumeric recognition, making it more suitable for enterprise voice systems.

6. Multimodal Input Support

GPT-Realtime-2.1 supports:

Input	Support
Text	✅
Audio	✅
Image	✅
Video	❌

Image input enables scenarios such as:

Visual customer support
Document interpretation
Camera-based assistants

GPT-Realtime-2.1 vs GPT-Realtime-2 vs GPT-4o Realtime

Model	Strength	Best Use
GPT-Realtime-2.1	Best realtime reasoning + voice agent capability	Production voice agents
GPT-Realtime-2	Strong realtime voice reasoning	Advanced conversational apps
GPT-4o Realtime	Fast multimodal interaction	General voice assistants

GPT-Realtime-2.1 vs GPT-Realtime-2

GPT-Realtime-2.1 improves:

Voice interruption recovery
Noise handling
Recognition accuracy
Conversational robustness

Both models share:

Speech-to-speech architecture
Tool calling
Reasoning support
Realtime API access

GPT-Realtime-2.1 vs GPT-4o Realtime

GPT-Realtime-2.1 is positioned for more advanced agent workflows.

Compared with GPT-4o Realtime:

Capability	GPT-Realtime-2.1	GPT-4o Realtime
Reasoning	Stronger	General
Context	128K	32K
Tool use	Supported	Supported
Voice agents	Advanced	General
Complex workflows	Better suited	Suitable

How to Use GPT-Realtime-2.1 API with CometAPI

Step 1: Get Your CometAPI API Key

Create a CometAPI account and generate an API token from the developer console.

Your API request should include:

Authorization: Bearer YOUR_COMETAPI_API_KEY
Content-Type: application/json

The API key authenticates your requests and allows your application to call available AI models through CometAPI.

Step 2: Create a GPT-Realtime-2.1 Session

GPT-Realtime-2.1 works through a persistent realtime session instead of traditional request-response chat completion.

A realtime session maintains:

Audio input stream
Model responses
Conversation state
Tool calls
Interruptions

OpenAI's Realtime API supports real-time communication through WebRTC, WebSocket, and SIP interfaces.

Example:

curl https://api.cometapi.com/v1/realtime/sessions \
-H "Authorization: Bearer YOUR_COMETAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '
{
  "model": "gpt-realtime-2.1",
  "modalities": [
    "audio",
    "text"
  ],
  "voice": "alloy",
  "instructions": "You are a helpful customer support voice assistant."
}
'

Example response:

{
  "id": "sess_xxxxx",
  "model": "gpt-realtime-2.1",
  "status": "active"
}

Step 3: Send Audio Input to GPT-Realtime-2.1

After creating a session, stream user audio.

Example workflow:

User microphone
        |
        ↓
Audio stream
        |
        ↓
GPT-Realtime-2.1
        |
        ↓
Generated voice response

Audio input can include:

Phone conversations
Voice commands
Customer support calls
Interactive assistants

GPT-Realtime-2.1 improves speech interaction with better silence detection, noise handling, and interruption behavior compared with earlier realtime models.

Step 4: Receive Real-Time Audio Responses

The model returns generated audio responses through the realtime connection.

Example event:

{
  "type": "response.audio.delta",
  "delta": "base64_audio_chunk"
}

Your application can immediately play received audio chunks.

Typical implementations:

WebRTC voice applications
Browser-based assistants
Mobile voice apps
AI phone agents

Step 5: Add Function Calling for Voice Agents

GPT-Realtime-2.1 supports function calling, allowing voice agents to execute external actions.

Example:

{
  "tools": [
    {
      "type": "function",
      "name": "check_order_status",
      "description": "Retrieve customer order information",
      "parameters": {
        "type": "object",
        "properties": {
          "order_id": {
            "type": "string"
          }
        }
      }
    }
  ]
}

Possible voice-agent workflows:

"Where is my package?"
"Book me a meeting tomorrow."
"Cancel my subscription."
"Check my account balance."

The model can recognize the request, call the appropriate tool, and continue the conversation naturally.

Step 6: Configure Reasoning and Instructions

GPT-Realtime-2.1 supports configurable reasoning effort.

Example:

{
  "model": "gpt-realtime-2.1",
  "reasoning": {
    "effort": "medium"
  },
  "instructions": "Act as a professional travel assistant."
}

Recommended settings:

Application	Reasoning Level
Simple voice commands	Low
Customer support	Medium
Complex workflow agents	High

FAQ

API

Copy a working endpoint and code example, then open the complete API reference when you need every parameter.

One API, production-ready model access

Authenticate once, call the model endpoint and keep the same billing and observability workflow across providers.

GET/v1/realtime

Sample code and API for GPT-Realtime-2.1

GET

/v1/realtime

set -euo pipefail

# curl can perform the HTTP Upgrade handshake and print the Realtime WebSocket
# byte stream. Use the Python or JavaScript example to send framed events.
WEBSOCKET_KEY="$(openssl rand -base64 16)"

curl --http1.1 --include --no-buffer \
  --request GET \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "OpenAI-Beta: realtime=v1" \
  --header "Connection: Upgrade" \
  --header "Upgrade: websocket" \
  --header "Sec-WebSocket-Version: 13" \
  --header "Sec-WebSocket-Key: ${WEBSOCKET_KEY}" \
  "https://api.cometapi.com/v1/realtime""?model=gpt-realtime-2.1"

cURL Code Example

set -euo pipefail

# curl can perform the HTTP Upgrade handshake and print the Realtime WebSocket
# byte stream. Use the Python or JavaScript example to send framed events.
WEBSOCKET_KEY="$(openssl rand -base64 16)"

curl --http1.1 --include --no-buffer \
  --request GET \
  --header "Authorization: Bearer $COMETAPI_KEY" \
  --header "OpenAI-Beta: realtime=v1" \
  --header "Connection: Upgrade" \
  --header "Upgrade: websocket" \
  --header "Sec-WebSocket-Version: 13" \
  --header "Sec-WebSocket-Key: ${WEBSOCKET_KEY}" \
  "https://api.cometapi.com/v1/realtime""?model=gpt-realtime-2.1"

Python Code Example

"""Send one text turn to gpt-realtime-2.1 over the Realtime WebSocket API.

Install the client with: pip install websocket-client
"""

import json
import os
from urllib.parse import urlencode

from websocket import create_connection


MODEL = "gpt-realtime-2.1"
BASE_URL = "wss://api.cometapi.com"
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"


def get(path: str) -> str:
    """Build a WebSocket URL for the API's GET route."""

    return f"{BASE_URL}{path}?{urlencode({'model': MODEL})}"


socket = create_connection(
    get("/v1/realtime"),
    header=[
        f"Authorization: Bearer {COMETAPI_KEY}",
        "OpenAI-Beta: realtime=v1",
    ],
    timeout=30,
)

try:
    socket.send(
        json.dumps(
            {
                "type": "session.update",
                "session": {
                    "modalities": ["text"],
                    "instructions": "Answer clearly and concisely.",
                },
            }
        )
    )
    socket.send(
        json.dumps(
            {
                "type": "conversation.item.create",
                "item": {
                    "type": "message",
                    "role": "user",
                    "content": [
                        {
                            "type": "input_text",
                            "text": "Give me one tip for a productive meeting.",
                        }
                    ],
                },
            }
        )
    )
    socket.send(json.dumps({"type": "response.create"}))

    while True:
        event = json.loads(socket.recv())
        event_type = event.get("type")
        if event_type in {
            "response.text.delta",
            "response.output_text.delta",
            "response.audio_transcript.delta",
            "response.output_audio_transcript.delta",
        }:
            print(event.get("delta", ""), end="", flush=True)
        elif event_type == "error":
            raise RuntimeError(json.dumps(event.get("error", event), indent=2))
        elif event_type == "response.done":
            print()
            break
finally:
    socket.close()

JavaScript Code Example

// Send one text turn to gpt-realtime-2.1 over the Realtime WebSocket API.
// Requires Node.js 22 or newer, which includes a global WebSocket client.

const model = "gpt-realtime-2.1";
const baseUrl = "wss://api.cometapi.com";
const apiKey = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";

function get(path) {
  const url = new URL(`${baseUrl}${path}`);
  url.searchParams.set("model", model);
  return url;
}

const socket = new WebSocket(get("/v1/realtime"), [
  "realtime",
  `openai-insecure-api-key.${apiKey}`,
  "openai-beta.realtime-v1",
]);

socket.addEventListener("open", () => {
  socket.send(
    JSON.stringify({
      type: "session.update",
      session: {
        modalities: ["text"],
        instructions: "Answer clearly and concisely.",
      },
    }),
  );
  socket.send(
    JSON.stringify({
      type: "conversation.item.create",
      item: {
        type: "message",
        role: "user",
        content: [
          {
            type: "input_text",
            text: "Give me one tip for a productive meeting.",
          },
        ],
      },
    }),
  );
  socket.send(JSON.stringify({ type: "response.create" }));
});

socket.addEventListener("message", ({ data }) => {
  const event = JSON.parse(data.toString());
  if (
    [
      "response.text.delta",
      "response.output_text.delta",
      "response.audio_transcript.delta",
      "response.output_audio_transcript.delta",
    ].includes(event.type)
  ) {
    process.stdout.write(event.delta || "");
  } else if (event.type === "error") {
    console.error(JSON.stringify(event.error || event, null, 2));
    socket.close();
    process.exitCode = 1;
  } else if (event.type === "response.done") {
    process.stdout.write("\n");
    socket.close();
  }
});

socket.addEventListener("error", (error) => {
  console.error("WebSocket error:", error.message || error);
  process.exitCode = 1;
});

Capabilities

Scan the model facts that matter before you choose an architecture or estimate production workload.

Supported capabilities

Features returned by the existing model API.

text-to-speech

Input and output

Inputs

text

Outputs

audio

Production profile

Provider: OpenAI
Context: Model specific
Commercial use: Supported

Use cases

Use GPT-Realtime-2.1 for production workflows that match its audio capabilities, then compare alternatives before committing to a long-term integration.

Speech, music and audio generation

Voice experiences and media production

Automated audio workflows at scale

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Uptime

Review live heartbeat data, endpoint availability and observed response times before moving into production.

Uptime

Request success rate over the last 30 days, reflecting the reliability of each model provider. CometAPI monitors all connected providers in real time, 24/7.

Respond

2010msAvg. Response

Uptime

70.2%Avg. Uptime

Versions

Review available model identifiers before pinning a production integration.

gpt-realtime-2.1

gpt-realtime-2.1-mini

Updates

Follow meaningful availability, pricing and capability changes for GPT-Realtime-2.1 without losing the stable model page.

Model changelog

One page that gets stronger over time.

Release notes, pricing changes, benchmark updates and migration guidance accumulate here while the canonical URL stays unchanged.

Aug 7, 2026

API availability confirmed

GPT-Realtime-2.1 is available through the CometAPI model catalog and API documentation.

Current

Live data

Pricing and limits synced from the catalog

Price, context, availability and limits are treated as dynamic properties instead of being embedded in the page title or model identity.

Aug 7, 2026

Permanent model entity created

The provider and model slug form a durable canonical URL; future content and data updates remain on this page.

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