VidgoAI

GPT 5.6 Sol API

openai/gpt-5.6-sol
1M tokens · 280 input credits / 1M tokens

GPT 5.6 Sol turns prompts and conversation context into detailed text for complex reasoning, multi-file software work, agent planning, and research synthesis. Choose it when task depth and careful constraint handling matter more than minimizing token cost.

GPT 5.6 Sol

OpenAI · responses

Chat with GPT 5.6 Sol

Each model has its own conversation. Switching never sends another model's history, and switching back resumes where you left off. Requests are billed from actual token usage.

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GPT 5.6 TerraGPT 5.6 LunaKimi K3

GPT 5.6 Sol

GPT 5.6 Sol accepts a text string or ordered message array and returns generated text plus usage in synchronous JSON or SSE. Give it complete code, evidence, and decision constraints when a task requires deep reasoning across many related inputs.

Why Choose This?

  • Deep multi-step reasoningProvide interdependent requirements and evidence for analysis that must track constraints across several decisions.

  • Complex software workUse repository context, architecture rules, and failure cases to plan or review changes spanning multiple files.

  • Long-horizon agent planningDescribe tools, checkpoints, and acceptance criteria to produce an executable plan for sustained workflows.

Parameters

ParameterRequirementDescription
inputRequired

A text string or ordered message array containing the task, supporting context, and conversation history.

max_output_tokensOptional

Sets the maximum number of tokens the model may return for this response.

streamOptional

Set false for synchronous JSON or true for an ordered SSE event stream.

Defaultfalsetrue

How to Use

  1. Frame the hard decisionState the objective, non-negotiable constraints, and failure modes Sol must account for.

  2. Supply complete working contextInclude the related code, evidence, dependencies, and prior decisions needed to reason across the task.

  3. Define the deliverableSpecify the required structure, assumptions, citations, or verification steps for the returned text.

  4. Review the acceptance criteriaCheck the answer against every constraint and refine missing context before using it in execution.

Pricing

Vidgo AI meters input, output, cache-read, and cache-write tokens separately, then settles their sum in credits. Rates below are per 1M tokens.

UsageRateDetails
Input tokens280 credits / 1M tokensInput usage that does not hit prompt cache.
Output tokens1680 credits / 1M tokensTokens generated by the model.
Cache read28 credits / 1M tokensInput tokens read from prompt cache.
Cache write350 credits / 1M tokensInput tokens written to prompt cache.

Best Use Cases

  • Cross-repository architecture reviewCombine source files, service boundaries, and failure reports to produce a change plan and review checklist.

  • Research decision memoTurn papers, reports, and competing requirements into findings, uncertainties, and a documented recommendation.

  • Multi-stage agent runbookConvert a complex objective, tool inventory, and completion rules into checkpoints for a long-running workflow.

Pro Tips

  • Separate non-negotiable constraints from preferences so Sol can prioritize them explicitly during multi-step reasoning.
  • Ask for assumptions, unresolved risks, and verification steps when the response will drive a broad software or research decision.
  • Keep repeated instructions and reference context unchanged across related requests to improve prompt-cache reuse.

Notes

  • The context window is 1M tokens, and the maximum output is 128K tokens.
  • GPT 5.6 Sol uses /v1/responses on Vidgo AI.
  • The minimum positive charge for a successful request is 0.001 credit; requests without valid output are not charged.
  • If a provider returns valid content without usage, the backend estimates token usage for settlement.

Related Models

GPT 5.6 TerraOpenAI · 1M tokensGPT 5.6 Terra text generation API from 112 credits per 1M input tokens.
GPT 5.6 LunaOpenAI · 1M tokensGPT 5.6 Luna text generation API from 11.2 credits per 1M input tokens.
Kimi K3Moonshot AI · 1,048,576 tokensKimi K3 text generation API from 456 credits per 1M input tokens.
Claude Opus 5Anthropic · 1M tokensClaude Opus 5 text generation API from 400 credits per 1M input tokens.
Claude Sonnet 5Anthropic · 1M tokensClaude Sonnet 5 text generation API from 170 credits per 1M input tokens.

GPT 5.6 Sol API — Frequently asked questions

What is the GPT 5.6 Sol API?

GPT 5.6 Sol is developed by OpenAI. It accepts text or conversation messages and returns generated text plus usage through Vidgo AI.

How do I call the GPT 5.6 Sol API?

Send a Bearer-authenticated POST request to /v1/responses with model gpt-5-6-sol and valid input. Use stream: false for JSON or stream: true for SSE.

How much does GPT 5.6 Sol cost?

Per 1M tokens, Vidgo charges 280 credits for input, 1680 for output, 28 for cache reads, and 350 for cache writes. The minimum positive charge for a successful request is 0.001 credit.

What inputs does GPT 5.6 Sol accept?

The Responses endpoint accepts input as a text string or message array. You can also set max_output_tokens and choose synchronous JSON or SSE with stream.

Which GPT 5.6 tier should I choose?

Choose Sol for the most demanding reasoning, software, agent, and research work. Choose Terra for balanced recurring production tasks or Luna for routine, high-volume text processing at lower Vidgo token rates.