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Text · Released Sep 2026

OpenAI GPT 6 Sol

OpenAI's cost-efficient high-end GPT-6 tier for demanding coding and agentic work, with vision and a 1M-token context window.

GPT 6 Sol is a cloud text model built by OpenAI. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 1.05M input tokens and up to 128K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions. It runs through OpenRouter and OpenAI using your own API key, from $2.00 per million input tokens.

Modality
Text
Available on
Model ID
openai/gpt-6-sol
Specs
Released
this month (Sep 2026)
Pricing
$2.00 / 1M in · $10.00 / 1M out
Inputs
Text, Images
Context window
1.05M in · 128K out
Reasoning
Adjustable effort
Controls
System prompt
Samples

Examples

Generated with GPT 6 Sol via OpenRouter. The same three prompts run against every text model in the catalog, shown verbatim, so the only thing that changes between two models’ answers is the model.

Short answer44 / 50 words

Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.

An API is a way for two computer programs to communicate. It lets one program request information or an action from another. For example, a weather app can use an API to get a forecast without needing to know how the weather service works.

Medium answer75 / 150 words

A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.

Use a hosted authentication provider. For a two-person startup, building and maintaining secure login, password recovery, multifactor authentication, and abuse protection would consume time better spent on the product. Choose a provider that supports standard protocols and lets you export user data. The strongest argument against this is dependence on a vendor for a critical part of your product. If its pricing rises or its service deteriorates, moving users elsewhere can be difficult and disruptive.

Long answer205 / 190–220 words

Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.

AI costs are difficult to forecast because usage rarely stays where a pilot suggests it will. Once employees find useful applications, more teams adopt them, and automated systems may make many more requests than people expect. A popular customer feature can turn every new user into recurring processing expense. The price of each request also varies. Longer conversations, larger documents, more capable models, and extra steps such as searching records all consume more computing power. Even when request counts are stable, a change in workflow can raise the bill. Suppliers can change prices, and capacity commitments or minimum charges may add surprises. Costs extend beyond the model itself. Preparing data, connecting systems, protecting sensitive information, monitoring quality, and paying staff or consultants can outweigh initial software fees. Failed experiments and compliance requirements also consume budgets. To regain control, set a budget for each use case and assign an owner. Track requests, average cost per task, and supporting costs weekly. Require approval before scaling pilots; set spending alerts and monthly limits where available. Test cheaper models for routine work and reserve expensive ones for tasks where they measurably improve results. Forecast a range of adoption scenarios, revisit it monthly, and stop projects whose benefits lag costs.

About the creator

OpenAI

OpenAI builds GPT, DALL·E, the Sora family, and the open-weight gpt-oss models, and has been a central force behind the modern wave of generative AI.

openai.com ↗
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