OpenAI/gpt-5.6-luna-web-search

gpt-5.6-luna-web-search

Free to try GPT 5.6 Luna Web Search API for fast current research, monitoring, validation, grounded answers, and affordable high-volume workflows.

Web Search

Related Gpt 5.6 Luna Models

gpt-5.6-luna-text-to-texttext-to-text

gpt-5.6-luna-image-to-textimage-to-text

gpt-5.6-luna-file-analysisfile-analysis

gpt-5.6-luna-web-searchweb-search

Documentation

API Examples

JavaScriptPythoncURL

Submit Example

const response = await fetch('https://api.flaq.ai/api/v1/chat/completions', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer YOUR_API_KEY',
    Accept: 'text/event-stream',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gpt-5.6-luna-web-search',
    messages: [
      {
        role: 'user',
        content: 'Find the latest public information about Flaq AI and summarize it for a product brief.'
      }
    ],
    stream: true,
    max_tokens: 2048
  })
});

const reader = response.body.getReader();
const decoder = new TextDecoder();
let buffer = '';
let assistantText = '';

while (true) {
  const { done, value } = await reader.read();
  if (done) break;

  buffer += decoder.decode(value, { stream: true });
  const frames = buffer.split('\n\n');
  buffer = frames.pop() || '';

  for (const frame of frames) {
    const lines = frame.split('\n').filter(Boolean);
    let eventName = 'message';
    const dataLines = [];

    for (const line of lines) {
      if (line.startsWith('event:')) {
        eventName = line.slice(6).trim();
      } else if (line.startsWith('data:')) {
        dataLines.push(line.replace(/^data:\s*/, ''));
      }
    }

    const raw = dataLines.join('\n').trim();
    if (raw === '[DONE]') {
      console.log('\nFinal text:', assistantText);
      continue;
    }

    let payload;
    try {
      payload = JSON.parse(raw);
    } catch {
      continue;
    }

    if (eventName === 'error' || payload.error) {
      const msg = payload.error?.message ?? payload.message ?? 'Chat request failed';
      throw new Error(msg);
    }

    const delta = payload.choices?.[0]?.delta;
    if (delta?.content) {
      assistantText += delta.content;
      console.log(assistantText);
    }
  }
}

Submit Example

import json
import requests

response = requests.post(
    'https://api.flaq.ai/api/v1/chat/completions',
    headers={
        'Authorization': 'Bearer YOUR_API_KEY',
        'Accept': 'text/event-stream',
        'Content-Type': 'application/json',
    },
    json={
        'model': 'gpt-5.6-luna-web-search',
        'messages': [
            {
                'role': 'user',
                'content': 'Find the latest public information about Flaq AI and summarize it for a product brief.',
            }
        ],
        'stream': True,
        'max_tokens': 2048,
    },
    stream=True,
)

response.raise_for_status()

event_name = 'message'
assistant_text = ''

for raw_line in response.iter_lines(decode_unicode=True):
    if not raw_line:
        event_name = 'message'
        continue

    if raw_line.startswith('event:'):
        event_name = raw_line.replace('event:', '', 1).strip()
        continue

    if raw_line.startswith('data:'):
        raw_data = raw_line.replace('data:', '', 1).strip()
        if raw_data == '[DONE]':
            print('\nFinal text:', assistant_text)
            continue

        payload = json.loads(raw_data)

        if event_name == 'error' or payload.get('error'):
            error = payload.get('error') or payload
            raise RuntimeError(error.get('message', 'Chat request failed'))

        choices = payload.get('choices') or []
        if choices:
            delta = choices[0].get('delta') or {}
            content = delta.get('content')
            if content:
                assistant_text += content
                print(content, end='', flush=True)

Submit Example

curl -N -X POST "https://api.flaq.ai/api/v1/chat/completions" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Accept: text/event-stream" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-5.6-luna-web-search",
    "messages": [
      {
        "role": "user",
        "content": "Find the latest public information about Flaq AI and summarize it for a product brief."
      }
    ],
    "stream": true,
    "max_tokens": 2048
  }'

Start a new chat

Send a message to begin.

GPT 5.6 Luna Web Search Pricing

Parameters	Price	Original Price	Discount

Token: input	$1.0000 per 1M input tokens	-	Standard
Token: output	$6.0000 per 1M output tokens	-	Standard

README

Fast & Affordable GPT 5.6 Luna Web Search API (Efficient OpenAI Search Integration)

GPT 5.6 Luna Web Search API on Flaq AI combines OpenAI's fastest GPT-5.6 model with access to current public web information. This cost-efficient search integration helps developers build responsive research, monitoring, validation, and content workflows that need fresh context at scale. With conversational follow-up and support for relevant multimodal inputs, Luna provides a practical way to add search-grounded answers without assembling separate retrieval infrastructure.

Key Features of GPT 5.6 Luna Web Search API

Fast Search-Grounded Responses: Combine web lookup with OpenAI's fastest GPT-5.6 model for responsive current-information workflows.
High-Volume Web Research: Support recurring monitoring, validation, and summary tasks with strong operating efficiency.
Current Information Lookup: Ground responses in recent public information for time-sensitive questions and updates.
Multimodal Research Context: Add supported image or file inputs when a search task needs additional visual or document context.
Conversation-Aware Follow-Up: Refine questions and continue exploring findings while retaining useful prior context.
Streaming API Integration: Deliver search-grounded responses progressively through a stable chat completion workflow.

How to Use GPT 5.6 Luna Web Search API on Flaq AI

Input: Natural-language research questions with optional supported images, files, and conversation context.
Output: Current, search-grounded answers and summaries generated through Flaq AI's web-enabled chat workflow.
Route Configuration: Designed for fast current-information lookup, monitoring, and contextual follow-up.
Configuration: Use supported context and output-length controls to guide the scope of each response.
Capabilities: Web lookup, current-event summaries, market monitoring, fact checking, and scalable search-grounded assistance through OpenAI API integration.

Best Use Cases for GPT 5.6 Luna Web Search API Integration

Automated Market Monitoring: Track public product, competitor, and industry updates across recurring workflows.
News & Trend Summaries: Produce timely overviews of current events and emerging topics for content or business teams.
Fast Fact Validation: Check public claims and reduce stale-information risk in high-volume knowledge applications.
Content Research Pipelines: Gather current topic context and generate concise research notes for publishing teams.
Sales Intelligence at Scale: Collect recent company and market context before outreach, prioritization, and account review.

Note Please ensure your prompts, uploaded inputs, and application workflows comply with OpenAI's safety and usage guidelines. If an error occurs, review the inputs for restricted content, simplify the request, and try again.

GPT 5.6 Luna Web Search vs Competitors: Comparative Analysis

GPT 5.6 Luna vs. GPT 5.6 Sol
GPT 5.6 Sol is designed for complex investigations that need flagship reasoning depth. GPT 5.6 Luna prioritizes faster and more cost-efficient web research at scale.
GPT 5.6 Luna vs. GPT 5.6 Terra
GPT 5.6 Terra balances strong professional search reasoning with cost. GPT 5.6 Luna focuses more directly on speed and high-throughput efficiency.
GPT 5.6 Luna vs. GPT 5.5 Web Search
GPT 5.5 supports dependable search-grounded workflows for professional applications. GPT 5.6 Luna provides a faster, cost-efficient option for recurring current-information tasks.
GPT 5.6 Luna vs. Gemini Search Workflows
Gemini search experiences align naturally with Google's ecosystem. GPT 5.6 Luna offers an efficient OpenAI-native route for scalable web research.
GPT 5.6 Luna vs. Traditional Search Pipelines
Traditional pipelines require separate retrieval, ranking, and synthesis components. GPT 5.6 Luna combines search-grounded assistance in a managed Flaq AI API workflow.