Audience
Software developers, AI engineers, autonomous agent developers, business professionals, enterprise automation teams, data analysts, researchers, designers, financial operations teams, and organizations seeking cost-efficient visual reasoning, computer-use automation, software development assistance, document analysis, and high-volume AI-powered workflows
About GPT-6.1 Terra
GPT-6.1 Terra is a multimodal artificial intelligence model developed by OpenAI for visual reasoning, computer use, software development, and professional productivity tasks. The model combines image understanding, natural language processing, and precise interaction with graphical applications to execute complex workflows. Its visual reasoning capabilities support interpreting technical drawings, analyzing images, understanding application interfaces, and extracting information from documents. GPT-6.1 Terra can automate computer-based tasks such as completing forms, entering invoice information into accounting software, editing videos, and manipulating application interfaces. The model supports a context window of 1,050,000 tokens, configurable reasoning effort, function calling, structured outputs, and integrations with external tools through the OpenAI API.
Pricing
Output: $5 per 1 million tokens
Cached Input: $0.05 per 1 million cached input tokens
Company Information
Videos and Screen Captures
Product Details
GPT-6.1 Terra Frequently Asked Questions
GPT-6.1 Terra Product Features
GPT-6.1 Terra Verified User Reviews
Write a Review-
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"Great model" Posted 2026-10-26
Pros: Great for the stuff where I want more than a lightweight model, but I don’t really need to bring out Sol or Astra. That middle ground is where it works really well. It feels fast, and it is especially good with screenshots, browser-based tasks, computer use, and smaller coding jobs. I can throw a UI problem or a multi-step workflow at it and usually get something useful without much back-and-forth. The 1M+ context window is also nice because I do not have to be precious about what I include. I can give it a bunch of files, logs, docs, or prior context and just let it work through the whole thing.
Cons: The main drawback is that it is a bit of a “middle child” model. Luna is cheaper when I just need something fast, and Sol is better when the task is genuinely hard.
Overall: It is quick, capable, reasonably priced, and really good for everyday agent work where I want a little more intelligence without paying for the top model every time.
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