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OpenAI GPT 5.6 Sol: AI Large Language Models

Generate text with OpenAI's GPT 5.6 Sol flagship. Deep reasoning for math, code, and scientific research. No subscription. GPT 5.6 Sol is OpenAI's flagship reasoning model, optimized for complex math, programming, and scientific research. Supports mixed text and image inputs, adjustable reasoning effort, and integrated web search tools. Pricing: $10.00/M input tokens, $60.00/M output tokens.

Interactive model controls

GPT 5.6 Sol is OpenAI's flagship reasoning model, optimized for complex math, programming, and scientific research. Supports mixed text and image inputs, adjustable reasoning effort, and integrated web search tools. Pricing: $10.00/M input tokens, $60.00/M output tokens.

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Overview

About this model

GPT 5.6 Sol is OpenAI's flagship reasoning model in the GPT 5.6 family, optimized for complex mathematics, programming, and scientific research. It accepts mixed text and image inputs, supports a system prompt to steer behavior, and can call an integrated web search tool for real-time information. Reasoning depth is adjustable via the reasoning_effort parameter, up to 'xhigh' for the most demanding logic problems. Sol delivers the deepest reasoning in the family, sitting above the speed-optimized Luna and the balanced Terra model.

1Advanced Reasoning: Solve highly complex mathematics, programming, and logic puzzles.
2Scientific Research: Analyze technical papers, datasets, and diagrams that require deep domain reasoning.
3Code Generation and Review: Produce and debug complex code that needs careful step-by-step logic.
4High-Stakes Analysis: Handle tasks where response quality matters more than speed or cost.
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Pricing & Value

Cost analysis

muapiapp$10.00/M input, $60.00/M output

Token-based billing. Minimum $0.0008 per call.

OpenAI (official)$5.00/M input, $30.00/M output

Official pricing for the flagship model. Muapiapp matches the official price without a markup on the underlying model tier.

ReplicateNot available

No dedicated GPT 5.6 Sol endpoint at this time.

** Competitor pricing is estimated based on similar model architectures and usage tiers.

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Technical Details

Configuration schema

Promptstring

The user message or instruction.

Default ValueSolve this complex math puzzle step by step.
Image URLstring

Optional image URL for multimodal requests.

Default Valueundefined
System Promptstring

Optional system-level instruction to guide model behavior.

Default ValueYou are an expert mathematician.
Web Search Switchboolean

Enable web search tool for real-time information retrieval.

Default Valuefalse
Reasoning EffortEnum (4 options)

Level of reasoning depth: low, medium, high, or xhigh.

Default Valuelow
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Implementation Guide

Developer documentation

Standard (Async)

POST /api/v1/gpt-5-6-sol — returns request_id, poll for result via /api/v1/predictions/{id}/result.

Streaming (SSE)

POST /api/v1/gpt-5-6-sol/stream — returns a live Server-Sent Events stream (Content-Type: text/event-stream). Each chunk has the format data: {"choices":[{"delta":{"content":"text"}}]}, ending with data: [DONE].

cURL Example

curl -X POST "https://api.muapi.ai/api/v1/gpt-5-6-sol" \
  -H "Authorization: Bearer $YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Solve this complex math puzzle step by step.",
    "reasoning_effort": "xhigh"
  }'
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Common Questions

Frequently asked

What is GPT 5.6 Sol best used for?

Sol is the flagship reasoning model in the GPT 5.6 family, optimized for complex mathematics, programming, and scientific research where depth of reasoning matters most.

How is pricing calculated for GPT 5.6 Sol?

Pricing is token-based at $10.00 per million input tokens and $60.00 per million output tokens, with a minimum charge of $0.0008 per call.

Does GPT 5.6 Sol support multimodal inputs?

Yes, Sol supports mixed text and image (image_url) inputs in a single message.

What is reasoning effort control?

You can control the depth of reasoning by passing a reasoning_effort value of 'low', 'medium', 'high', or 'xhigh'. Sol is designed to make the most of 'high' and 'xhigh' settings on demanding problems, though this increases latency.

How do I choose between async and streaming endpoints?

Use the streaming endpoint (/gpt-5-6-sol/stream) for interactive chat interfaces where the user expects real-time feedback. Use the async endpoint (/gpt-5-6-sol) for background tasks, workflows, and automated scripts.

When should I use Luna or Terra instead of Sol?

Use Luna for high-volume, low-latency classification tasks, or Terra for balanced general business and analytical work, when Sol's deeper reasoning isn't needed and you want to reduce cost.