OpenAI GPT 6 Astra
OpenAI's flagship GPT-6 model for complex reasoning, coding, research, and long-running agent work, with vision and a 1M-token context window.
From OpenAI, GPT 6 Astra is a cloud text model. 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 Runware, OpenRouter, and OpenAI using your own API key, from $10.00 per million input tokens.
- Released
- this month (Sep 2026)
- Pricing
- $10.00 / 1M in · $50.00 / 1M out
- Inputs
- Text, Images
- Context window
- 1.05M in · 128K out
- Reasoning
- Adjustable effort
- Controls
- System prompt
Examples
Generated with GPT 6 Astra via Runware. 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 computer program to request information or actions from another. It sets rules for what can be requested and how to ask. For example, a weather app uses an API to get forecasts from a weather service.
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 resets, multi-factor authentication, and abuse protections is usually a poor use of scarce engineering time. Authentication is critical infrastructure, but rarely what makes customers choose your product. Pick a provider with transparent pricing, standard protocols, and a documented migration path; you still need to configure it correctly and enforce authorization in your application. The strongest argument against this recommendation is vendor lock-in: authentication becomes deeply embedded in your product, so price increases, service restrictions, or an outage can leave you with little leverage. Migrating later may require substantial engineering work and force users through disruptive account-recovery or password-reset flows.
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 hard to predict because the bill depends less on how many employees have access than on what they ask the system to do. A short question may cost pennies; a complex task involving long documents, repeated attempts, or several automated steps can cost much more. As adoption grows, usage can rise faster than headcount. Prices and technology also change quickly. Vendors revise rates, introduce new models, and charge separately for storage, search, or data transfer. Switching providers may require costly integration work. Meanwhile, the advertised price rarely includes preparing company data, checking accuracy, protecting confidential information, training staff, and maintaining systems. Manage this uncertainty by budgeting for a range of outcomes rather than one forecast. Run limited pilots, measure total cost per completed business task, and compare that cost with the value delivered. Assign spending owners, set usage limits and alerts, and review bills monthly. Use cheaper models for routine work and reserve premium tools for tasks that justify them. Negotiate clear pricing and exit terms, maintain a contingency reserve, and release funding in stages as results become measurable. The goal is not perfectly predictable spending, but visible costs, controlled exposure, and evidence that additional investment produces worthwhile returns for the business.
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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