OpenAI/gpt-5.6-luna-text-to-text

gpt-5.6-luna-text-to-text

Free to try GPT 5.6 Luna API for fast chat, writing, coding, summaries, and affordable high-throughput OpenAI production workflows. Lower cost for coding than Claude Opus 4.8.

Text Chat

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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-text-to-text',
    messages: [
      {
        role: 'user',
        content: 'Write a concise product update for a developer audience.'
      }
    ],
    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-text-to-text',
        'messages': [
            {
                'role': 'user',
                'content': 'Write a concise product update for a developer audience.',
            }
        ],
        '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-text-to-text",
    "messages": [
      {
        "role": "user",
        "content": "Write a concise product update for a developer audience."
      }
    ],
    "stream": true,
    "max_tokens": 2048
  }'

Start a new chat

Send a message to begin.

GPT 5.6 Luna Text to Text 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 Text-to-Text API (OpenAI's Most Cost-Efficient GPT-5.6 Model)

GPT 5.6 Luna Text-to-Text API on Flaq AI delivers the fastest and most cost-efficient experience in OpenAI's GPT-5.6 family. Designed for responsive and high-throughput production workflows, Luna helps developers build chat, writing, summarization, coding, and knowledge features that need reliable output at scale. With multi-turn conversation context, streaming responses, and flexible output controls, teams can integrate GPT capabilities without managing model infrastructure or provider-specific plumbing.

Key Features of GPT 5.6 Luna Text-to-Text API

Fast GPT-5.6 Responses: Support responsive text experiences and time-sensitive application workflows with OpenAI's fastest GPT-5.6 model.
High-Throughput Production: Process recurring chat, writing, summarization, and classification-style tasks efficiently at scale.
Cost-Efficient Reasoning: Apply capable GPT reasoning to everyday workloads where predictable operating efficiency matters.
Reliable Instruction Following: Preserve requested tone, structure, constraints, and output goals across natural-language tasks.
Multi-Turn Conversation Context: Maintain useful context across follow-up messages for iterative assistance and refinement.
Streaming API Integration: Deliver text progressively through a stable chat completion workflow for responsive user experiences.

How to Use GPT 5.6 Luna Text-to-Text API on Flaq AI

Input: Natural-language prompts, system instructions, conversation history, and structured task requirements.
Output: High-quality text responses returned through streaming or standard chat completion workflows.
Route Configuration: Designed for fast text-only conversations with flexible context and follow-up support.
Configuration: Use supported context and output-length controls to guide response behavior for each task.
Capabilities: Conversational assistance, writing, summarization, coding support, multilingual content, and scalable text automation through OpenAI API integration.

Best Use Cases for GPT 5.6 Luna Text-to-Text API Integration

High-Volume Chat Assistants: Power responsive customer, product, and internal assistants across frequent interactions.
Content Operations: Generate summaries, drafts, descriptions, and reusable copy for recurring publishing workflows.
Developer Utilities: Create fast code explanations, documentation drafts, and routine engineering assistance.
Workflow Automation: Process structured text requests, transformations, and repetitive knowledge tasks efficiently.
Multilingual Applications: Generate and adapt content across languages for global, high-throughput products.

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

GPT 5.6 Luna Text-to-Text vs Competitors: Comparative Analysis

GPT 5.6 Luna vs. GPT 5.6 Sol
GPT 5.6 Sol is the flagship choice for the most complex reasoning workloads. GPT 5.6 Luna prioritizes faster, more cost-efficient text processing for scalable applications.
GPT 5.6 Luna vs. GPT 5.6 Terra
GPT 5.6 Terra balances strong professional capability with lower cost. GPT 5.6 Luna goes further toward speed and operating efficiency for high-throughput use.
GPT 5.6 Luna vs. GPT 5.5
GPT 5.5 supports complex professional work across a broad range of tasks. GPT 5.6 Luna provides a faster, more cost-efficient path for recurring production text workloads.
GPT 5.6 Luna vs. Claude Sonnet 5
Claude Sonnet 5 focuses on strong agentic reasoning and coding within the Anthropic ecosystem. GPT 5.6 Luna offers a fast OpenAI-native option for scalable text applications.
GPT 5.6 Luna vs. Open Models
Open models provide deployment control but require serving and optimization work. GPT 5.6 Luna offers managed, cost-efficient text generation through Flaq AI's API workflow.