OpenAI releases GPT-6.1 Terra: API prices halved while closing in on its larger models

What happened

OpenAI 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: $1 per million input tokens and $5 per million output tokens, versus $2 and $12 for GPT-5.6 Terra. Cached inputs drop to $0.05 per million tokens, a quarter of the previous rate. The model is available now in ChatGPT Work and Codex for Plus, Pro, Enterprise, and Edu users, and through the API.

Key details

• OpenAI positions Terra as its closest competitor to Anthropic's mid-tier Sonnet series at half the price: Claude Sonnet 5.5 charges $2/$10 for input/output tokens.
• Artificial Analysis calls it a new benchmark for intelligence per dollar: at maximum reasoning effort, it 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 7 to 13 points, placing it on the Pareto frontier. Its Intelligence Index score of 48 sits between GPT-6.1 Sol (52) and GPT-5.6 Terra (42).
• Hallucinations drop sharply: on the AA-Omniscience benchmark, the model guesses only 38 percent of the time when it lacks an answer, down from 88 percent, with accuracy up two points.
• In computer control, it matches GPT-6 Astra on Agents' Last Exam at one-tenth the token price; versus Claude Opus 5.5 it is over three times more token-efficient at a quarter of the token price, roughly nine times lower cost per task, and finishes more than three times faster than GPT-6 Astra and GPT-6.1 Sol.
• Coding improves markedly: on Terminal-Bench 4.0 it solves 50.3 percent of tasks at maximum effort, up from 21.5 percent, placing it in the same tier as GPT-6.1 Sol. For the most demanding coding tasks, OpenAI still recommends GPT-6.1 Sol and GPT-6 Astra.
• On safety, the model meets OpenAI's "Critical" cybersecurity threshold under the Preparedness Framework, inherits GPT-6 Astra's safeguards, and raises its indirect prompt injection defense rate from 96.2 percent to 98.8 percent.

Why it matters

The core of this release is cost-efficiency rather than raw performance. Terra scores below the larger GPT-6.1 Sol on the Intelligence Index, yet approaches larger models' results at a fraction of the cost across multiple benchmarks, even coming within five points of Claude Opus 5.5 on Terminal-Bench-Science 0.1 at less than a fifth of the estimated cost. Lower hallucination rates and stronger prompt injection defense, combined with faster execution, point the same way: mid-tier models are taking on more real work at lower cost.

Who it affects

Plus, Pro, Enterprise, and Edu users of ChatGPT Work, Codex, and the API benefit directly from the price cut. OpenAI targets everyday work tasks, from drafting proposals to interpreting technical drawings to filling out forms. Teams relying on automated software control and coding agents get a cheaper option, though OpenAI still recommends the larger Sol and Astra models for the hardest coding tasks.

Analysts frame Terra as a new point on the Pareto frontier, where cost and performance can no longer both improve simultaneously, which is the release's most noted industry takeaway.

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.

On the Intelligence Index (top), GPT-6.1 Terra scores 48, between GPT-6.1 Sol (52) and GPT-5.6 Terra (42). The cost-performance chart (bottom) shows that at lower effort levels, the model delivers the best current ratio of intelligence to cost per task. | Image: Artificial Analysis

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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