OpenAI has released GPT-6.1 Terra, a model it says pushes the cost-to-performance boundary further than any of its predecessors. API prices are half those of GPT-5.6 Terra.
Terra is OpenAI's closest competitor to Anthropic's mid-tier Sonnet series at half the price. Input tokens cost $1 per million, output tokens $5, compared to $2 and $10 for Claude Sonnet 5.5 and $2 and $12 for GPT-5.6 Terra. Cached inputs drop to just $0.05 per million tokens, a quarter of the previous rate.
According to OpenAI, the model combines fast visual reasoning with precise computer control and a more natural writing style, targeting everyday work tasks from drafting proposals to interpreting technical drawings to filling out forms. GPT-6.1 Terra is available now for Plus, Pro, Enterprise, and Edu users in ChatGPT Work and Codex, as well as through the API.
Analysts say cost efficiency has hit a new high
Artificial Analysis calls GPT-6.1 Terra a new benchmark for intelligence per dollar. At maximum reasoning effort, the model gains 6 points on the Intelligence Index over GPT-5.6 Terra while costing less than a third per task ($0.40 versus $1.40). At lower effort levels the gains are even larger—7 to 13 points—placing the model on the Pareto frontier, the point where cost and performance can no longer both improve simultaneously.
In the new Coding Agent Index v2.0, Terra scores 48, six points below GPT-6.1 Sol (54) and 17 points above GPT-6 Luna (31). The hallucination drop is even bigger. On the private AA-Omniscience benchmark, the model resorts to guessing only 38 percent of the time when it lacks the answer, down from 88 percent for GPT-5.6 Terra. Accuracy also rose by two points.
Computer control three times faster than the largest models
OpenAI positions GPT-6.1 Terra as particularly strong at automated software control. On the Agents' Last Exam benchmark, it matches GPT-6 Astra's performance at one-tenth the token price. Compared to Claude Opus 5.5 at maximum effort, Terra is more than three times as token-efficient at a quarter of the token price. That translates to roughly nine times lower cost per task. It also finishes more than three times faster than both GPT-6 Astra and GPT-6.1 Sol, the company says.
On MMMU-Pro for visual reasoning, GPT-6.1 Terra outperforms its predecessor at every reasoning level and nearly matches GPT-6 Astra and GPT-6.1 Sol. On the desktop agent benchmark OSWorld 2.1, it beats GPT-5.6 Terra's best result at medium effort for a fraction of the cost.
Terra also shows a sharp improvement in coding. On Terminal-Bench 4.0, GPT-6.1 Terra solves 50.3 percent of tasks at maximum reasoning effort, up from 21.5 percent for GPT-5.6 Terra. According to Artificial Analysis, that 20-point jump puts the model in the same tier as GPT-6.1 Sol. On the scientific coding benchmark Terminal-Bench-Science 0.1, Terra outperforms GPT-6.1 Sol at lower cost and comes within five points of Claude Opus 5.5 at less than a fifth of the estimated cost. For the most demanding coding tasks, however, OpenAI still recommends GPT-6.1 Sol and GPT-6 Astra.
Terra falls under OpenAI's "critical" safety threshold
GPT-6.1 Terra meets OpenAI's "Critical" cybersecurity threshold as defined by the company's Preparedness Framework and inherits the safeguards of GPT-6 Astra. Compared to its predecessor, the model is more likely to stay within its assigned boundaries and disclose restrictions to users.
According to the system card, GPT-6.1 Terra holds up about as well as GPT-6 Astra and GPT-6.1 Sol against direct attacks on the instruction hierarchy, with those models hitting 99.99 percent on such tests. For indirect prompt injection attacks, where malicious instructions are buried in third-party content, Terra's defense rate sits at 98.8 percent, up from 96.2 percent with GPT-5.6 Terra.
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