GPT-6.1 Terra meets OpenAI’s Critical cyber threshold, and it’s cheaper than GPT-5.6 Terra
OpenAI released GPT-6.1 Terra, a model that operates desktop software, to all Plus, Pro, Enterprise, and Edu users in ChatGPT Work and Codex, and to developers through its API as gpt-6.1-terra. API prices are 50 percent below those of GPT-5.6 Terra and GPT-6.1 Sol: $1 per million input tokens, $0.05 per million cached input tokens, and $5 per million output tokens. Tokens are the chunks of text a model reads and writes.
OpenAI says Terra meets the Critical threshold in cybersecurity under its Preparedness Framework and keeps the protections built for GPT-6 Astra. The company’s own example of high-volume work for Terra is reading incoming invoices and entering the details into accounting software.
What Critical means
Critical is the higher of two cybersecurity thresholds in the version of the Preparedness Framework dated April 2025. A model reaches it if, with tools, it can find and build working exploits for unknown software flaws, known as zero-days, of all severity levels in many hardened real-world critical systems with no human involved, or if it can plan and run a new attack from start to finish against a hardened target given nothing more than a high-level goal.
OpenAI’s rules require safeguards during development, whatever the release plans, and call for halting further development until safeguards meeting a Critical standard are specified. On September 1, 2026, OpenAI designated Astra as its first model at this level.
Prompt injection
OpenAI says Terra held up well in its prompt injection tests, which used malicious instructions meant to pull the model off the user’s task. Terra is more likely than GPT-5.6 Terra to stay within scope and to disclose limitations and blockers honestly.
What OpenAI measured
OpenAI measured Terra on Agents’ Last Exam, a benchmark of professional tasks that includes turning architectural drawings into a 3D model. At medium reasoning effort, Terra scores 15 percentage points above GPT-5.6 Terra at about one-third the cost, and OpenAI says it performs on par with GPT-6 Astra at one-tenth the price per token.
At max effort, OpenAI puts Terra at more than three times the token efficiency of Claude Opus 5.5 and one-fourth its price per token, which works out to a cost per task roughly nine times lower. Terra also completes tasks over three times faster than GPT-6 Astra and GPT-6.1 Sol.
On OpenAI’s internal benchmark of error-inducing prompts, Terra’s error rate at low reasoning effort fell from 53.6 percent with GPT-5.6 Terra to 16.7 percent, or one prompt in six. At maximum effort it fell 18 percentage points to 4.3 percent.
Hard coding tasks go elsewhere
On Terminal-Bench 4.0, which tests coding agents on command-line problems such as fixing a webpage whose layout shifts as it loads, Terra at maximum effort solves 50.3 percent of tasks. GPT-5.6 Terra’s published score is 21.5 percent. That leaves 49.7 percent of tasks unsolved, and OpenAI says GPT-6.1 Sol and GPT-6 Astra remain the better choice for the most complex coding tasks.
On Terminal-Bench-Science 0.1, which has agents use code for research tasks such as tracking cell divisions in a time-lapse video, Terra at max reasoning beats GPT-6.1 Sol at lower cost and comes within five points of Opus 5.5 at less than one-fifth the estimated cost.
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