OpenAI has released GPT-6.1 Terra, a fast, low-cost model built for computer use, visual reasoning, and clearer writing. It handles the tasks that fill a workday, like filling out forms, editing videos, and interpreting technical drawings, and it costs half as much as GPT-6.1 Sol through the API.
The announcement arrives about four weeks after GPT-6.1 Sol, and it upgrades the Terra tier that debuted with GPT-5.6. GPT-6.1 Terra is available starting today in ChatGPT Work and Codex.
GPT-6.1 Terra Costs $1 per Million Input Tokens and Is Live in ChatGPT Work and Codex
Standard API prices for GPT-6.1 Terra are 50 percent below both GPT-5.6 Terra and GPT-6.1 Sol. Per million tokens, the two newest models compare like this:
- GPT-6.1 Terra: $1 input, $5 output, $0.05 cached input
- GPT-6.1 Sol: $2 input, $10 output, $0.10 cached input
That makes high-volume jobs practical to automate, such as reading incoming invoices and entering the details into accounting software. Inside ChatGPT Work and Codex, the same usage allowance covers more tasks with Terra than with GPT-5.6 Terra, and substantially more than with GPT-6.1 Sol or GPT-6 Astra.
The model is open to Plus, Pro, Enterprise, and Edu users. Developers can call it in the API as gpt-6.1-terra.
GPT-6.1 Terra Matches GPT-6 Astra on Computer Use at One-Tenth the Price per Token
OpenAI measured computer use on Agents’ Last Exam, a benchmark of professional tasks such as turning architectural drawings into a 3D model or logging an animated film shot by shot for a restoration team. At medium reasoning effort, GPT-6.1 Terra scores 15 percentage points higher than GPT-5.6 Terra at about one-third the cost. It also lands on par with GPT-6 Astra at one-tenth of the price per token.
The rest of the computer-use results from OpenAI’s tests:
- At max effort, Terra is over three times as token efficient as Claude Opus 5.5 and costs one-fourth as much per token, which works out to roughly 9x lower cost per task.
- It completes tasks more than three times faster than both GPT-6 Astra and GPT-6.1 Sol.
- On MMMU-Pro, a visual reasoning benchmark, it beats GPT-5.6 Terra at every reasoning setting and nearly matches GPT-6 Astra and GPT-6.1 Sol.
- On OSWorld 2.1, which tests multistep tasks in desktop apps, it passes GPT-5.6 Terra’s best score at medium effort for a fraction of the cost per task.
GPT-6.1 Terra Cuts Its Error Rate to 16.7 Percent and More Than Doubles Its Coding Score
OpenAI ran an internal benchmark of error-inducing prompts to test hallucinations. At low reasoning effort, the error rate falls from 53.6 percent with GPT-5.6 Terra to 16.7 percent with GPT-6.1 Terra. At max effort it drops 18 points to 4.3 percent, close to the rates for GPT-6 Astra and GPT-6.1 Sol.
On Terminal-Bench 4.0, which has agents fix problems from the command line, GPT-6.1 Terra solves 50.3 percent of tasks at max effort, against the 21.5 percent GPT-5.6 Terra published. GPT-6.1 Sol and GPT-6 Astra remain the better choice for the most complex coding work.
On Terminal-Bench-Science 0.1, which has agents run code for research tasks like tracking cell divisions in a time-lapse video, Terra beats GPT-6.1 Sol at lower cost. It comes within five points of Claude Opus 5.5 at less than one-fifth the estimated cost.
Safeguards Carry Over from GPT-6 Astra
GPT-6.1 Terra is more likely than GPT-5.6 Terra to stay within scope and to disclose limitations and blockers to the user. It also held up well in OpenAI’s prompt-injection tests against malicious instructions meant to pull it off the user’s task.
The model meets the Critical threshold in cybersecurity under OpenAI’s Preparedness Framework, and it keeps the protections built for GPT-6 Astra.
