OpenAI/gpt-5.6-terra-text-to-text

gpt-5.6-terra-text-to-text

Free to try GPT 5.6 Terra API for balanced OpenAI reasoning, coding, writing, and dependable LLM workflows at a practical production cost.

Text Chat

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gpt-5.6-terra-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-terra-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-terra-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-terra-text-to-text",
    "messages": [
      {
        "role": "user",
        "content": "Write a concise product update for a developer audience."
      }
    ],
    "stream": true,
    "max_tokens": 2048
  }'

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Send a message to begin.

GPT 5.6 Terra Text to Text Pricing

Parameters	Price	Original Price	Discount

Token: input	$2.5000 per 1M input tokens	-	Standard
Token: output	$15.0000 per 1M output tokens	-	Standard

README

Balanced & Cost-Effective GPT 5.6 Terra Text-to-Text API (OpenAI Model for Professional Work)

GPT 5.6 Terra Text-to-Text API on Flaq AI provides a balanced OpenAI model for professional reasoning, coding, writing, and knowledge workflows. Positioned as the strong lower-cost option in the GPT-5.6 family, Terra helps developers build dependable text applications without defaulting to the flagship tier for every request. With multi-turn conversation context, streaming responses, and flexible output controls, teams can support everyday production workloads through a stable OpenAI API integration.

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

Balanced Professional Reasoning: Handle multi-step prompts, analysis, planning, and structured tasks with a practical balance of capability and cost.
Reliable Coding Assistance: Generate, explain, review, and debug code for common software development and technical documentation workflows.
Production Writing Quality: Create clear reports, summaries, emails, briefs, and long-form content from detailed instructions.
Consistent Instruction Following: Preserve requested tone, format, constraints, and objectives across professional text tasks.
Multi-Turn Conversation Context: Retain useful prior context for iterative drafting, refinement, and problem solving.
Streaming API Integration: Deliver responses progressively through a stable chat completion workflow for responsive applications.

How to Use GPT 5.6 Terra 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 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: Professional reasoning, coding support, writing, summarization, multilingual content, and conversational assistance through OpenAI API integration.

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

Everyday Developer Workflows: Draft code, explain systems, review implementation ideas, and produce technical documentation.
Business Writing & Analysis: Create reports, briefs, summaries, proposals, and internal communications with consistent structure.
Research & Knowledge Support: Compare information, organize findings, and generate useful synthesis for professional teams.
Customer Support Automation: Build context-aware assistants that answer questions and follow operational guidelines.
Scalable Content Production: Generate and adapt multilingual content for recurring publishing and communication workflows.

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 Terra Text-to-Text vs Competitors: Comparative Analysis

GPT 5.6 Terra vs. GPT 5.6 Sol
GPT 5.6 Sol is the flagship model for workloads that prioritize maximum capability. GPT 5.6 Terra offers a more balanced lower-cost option for broad professional text applications.
GPT 5.6 Terra vs. GPT 5.6 Luna
GPT 5.6 Luna prioritizes the fastest and most cost-efficient GPT-5.6 experience. GPT 5.6 Terra provides additional balance for tasks that need stronger everyday reasoning.
GPT 5.6 Terra vs. GPT 5.5
GPT 5.5 supports complex real-world work across coding, analysis, and writing. GPT 5.6 Terra is positioned as a competitive lower-cost path into the newer GPT family.
GPT 5.6 Terra vs. Claude Sonnet 5
Claude Sonnet 5 provides strong agentic reasoning and coding in the Anthropic ecosystem. GPT 5.6 Terra offers a balanced OpenAI-native alternative for production text workflows.
GPT 5.6 Terra vs. Gemini
Gemini models are attractive for Google-centered multimodal applications. GPT 5.6 Terra is suited to teams seeking balanced GPT reasoning through a familiar OpenAI API workflow.