OpenAI GPT 6 Sol Pro
GPT 6 Sol in OpenAI's pro reasoning mode, which works longer on each answer for higher quality on hard tasks.
GPT 6 Sol Pro 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 using your own API key, from $2.00 per million input tokens.
- 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
Examples
Generated with GPT 6 Sol Pro 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.
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 one app to request information or services from another. For example, a weather app can use an API to get a forecast from a weather provider without knowing how the provider’s system works.
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, MFA, and abuse protection will consume time better spent on the product. Choose a reputable provider that supports standard protocols and lets you export user data. The strongest argument against this choice is lock-in: once customers depend on that provider to log in, a price increase or service change can make switching providers expensive and disruptive.
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 spending is difficult to forecast because usage grows unevenly. A successful assistant may attract far more employees and customers than expected, while a quiet launch may cost little. Each conversation also varies in length and complexity, so the same number of users can produce very different bills. Costs can also change when teams switch models, add features such as document search, or let software agents make several calls to finish one task. Those choices may improve results, but they multiply computing, storage, and data-processing expenses. Prices and contracts can shift too, and providers may charge differently for input, output, and reserved capacity. Finally, the bill is not just the model. Security reviews, data cleanup, integration, monitoring, staff time, and compliance can outweigh usage charges. Experiments that become permanent services bring maintenance and support costs. Treat forecasts as ranges rather than promises. Track spending by product, team, and task, including the full cost of each workflow. Set usage limits and alerts, test cheaper models where quality permits, and require a business owner for each deployment. Start with small pilots, measure cost per useful outcome, and expand only when benefits justify it. Review assumptions monthly, because adoption and technology can change faster than annual company budgets.
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.
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