🔍 Read the full analysis: GPT-6.1 Terra Isn’t OpenAI’s Smartest Model. It May Be The Cheapest Way To Get The Job Done on ThorstenMeyerAI.com
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TL;DR
OpenAI released GPT-6.1 Terra on October 26, 2026, pricing API use at $1 per million input tokens and $5 per million output tokens. Artificial Analysis measured a range of scores and costs across its effort settings, finding low and medium effort on its cost-efficiency frontier; those independent results do not make Terra the top-scoring model.
OpenAI released GPT-6.1 Terra on October 26, pricing API use at $1 per million input tokens and $5 per million output tokens, half the listed price of its predecessor, GPT-5.6 Terra. Independent benchmarker Artificial Analysis measured Terra at 48.1 on its Intelligence Index at maximum effort, below several higher-scoring models, while finding its low and medium effort settings more cost-efficient on average task costs.
Terra is available in the API as gpt-6.1-terra and to eligible Plus, Pro, Enterprise and Edu users in ChatGPT Work and Codex, according to OpenAI. The company describes it as a fast, efficient model for workplace communication and computer-based tasks, including processing invoices and entering information into accounting software. OpenAI says the same ChatGPT allowance can cover substantially more tasks with Terra than with Sol or Astra.
Artificial Analysis reported a 48.1 Intelligence Index score and an average cost of $0.40 per evaluation task for Terra at maximum effort. Its comparison listed Claude Opus 5.5 at 57.6 and $5.98 per task, GPT-6.1 Sol at 51.8 and $0.72, and GPT-6 Luna at 38.1 and $0.07. These are averages across the benchmark’s evaluation tasks, not a guaranteed price for any individual customer’s work.
Terra has six effort settings, and the choice changes both measured performance and cost. Artificial Analysis put the range at 33 to 48 points and $0.05 to $0.40 per task; its data show maximum effort costs about 7.4 times as much as low effort for 12 additional points. The source reports that low and medium settings fall on the benchmark’s cost-efficiency frontier, while settings above them do not. It also reports that non-reasoning mode costs almost twice as much per task as low effort while scoring lower.
Infographic 01 · The effort curve
One model, six settings, a 7-fold cost range.
GPT-6.1 Terra at each effort level, as measured by Artificial Analysis. Low and medium sit on its cost-efficiency frontier: no tested model is both cheaper and better.
Score · Intelligence Index
independent higher is better
Cost per finished task
note the last step shorter is cheaper
All six settings
| Effort | Index | Cost / task | Output tokens / task | Hallucination rate |
|---|---|---|---|---|
| Non-reasoning | Index 33.5 | Cost $0.107 | Tokens 4,737 | Hallucination 72% |
| Low | Index 36.2 | Cost $0.055 | Tokens 2,681 | Hallucination 46% |
| Medium | Index 41.3 | Cost $0.095 | Tokens 5,835 | Hallucination 44% |
| High | Index 43.9 | Cost $0.134 | Tokens 9,027 | Hallucination 43% |
| Xhigh | Index 45.4 | Cost $0.194 | Tokens 14,551 | Hallucination 42% |
| Max | Index 48.1 | Cost $0.403 | Tokens 35,096 | Hallucination 38% |
Hallucination rate in AA-Omniscience: how often the model answers anyway when it does not know. Lower is better.
The first steps up are cheap. The last one doubles the bill.Assessment: Thorsten Meyer
Sources: Artificial Analysis model pages (retrieved 26 Oct 2026); Artificial Analysis launch article (26 Oct 2026). Cost per task is the average across the index’s evaluation tasks.
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Why Task Costs Change the Choice
Terra’s launch highlights a gap between token prices and the cost of completing a task. A model with a lower price per token can still cost more to finish a job if it uses more tokens. Artificial Analysis’s results show Terra at low effort averaging fewer output tokens per task than its non-reasoning mode, alongside a lower reported task cost. That makes task-level measurement relevant to companies comparing models for repeated workflows.
The trade-off is capability. Terra’s maximum-effort score is below the scores reported for several competing models, and OpenAI says its own evaluation indicates that Sol and Astra remain better choices for the most complex coding tasks. For users and developers, the results support testing a smaller or lower-effort option on routine work while retaining stronger models for difficult cases. Actual savings will depend on task mix, prompt length, retries and the amount of reasoning required.
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Terra in OpenAI’s Model Lineup
OpenAI positions Terra between GPT-6 Luna and the larger Sol and Astra models. Its listed API prices are $1 per million input tokens and $5 per million output tokens, compared with $2 and $12 for GPT-5.6 Terra. Cached input is listed at $0.05 per million tokens. Artificial Analysis’s model pages, retrieved October 26, 2026, list these prices and calculate task cost from average spending across its evaluation set.
The launch material includes company-run tests as well as the independent benchmark. OpenAI says Terra scored 57.6% at medium effort on Agents’ Last Exam, compared with 42.6% for GPT-5.6 Terra at medium, and reports costs of $0.29 and $0.84 per task respectively. On Terminal-Bench 4.0, OpenAI reports a 50.3% result at maximum effort for Terra, against a published 21.5% for GPT-5.6 Terra. These are OpenAI’s own reported measurements, and should not be conflated with Artificial Analysis’s separate Intelligence Index.
What the Benchmarks Do Not Show
The available figures do not establish what Terra will cost or how well it will perform for a particular customer. Artificial Analysis’s task costs are averages across its own evaluation set; results can differ with workload, usage patterns and settings. The supplied launch-day data also do not include an independent speed measurement for Terra. OpenAI says Terra completes tasks more than three times faster than Astra and Sol, but that speed claim is from the company and was not independently measured in the cited material.
Some comparisons also come from different tests and should not be treated as directly interchangeable. OpenAI’s computer-use and coding results use named benchmarks, while Artificial Analysis’s Intelligence Index combines ten evaluations. OpenAI also says Terra meets the Critical threshold for cybersecurity under its Preparedness Framework; that is the company’s classification. The source material does not provide details sufficient to independently assess the classification or its practical implications.
Testing Terra on Real Workloads
The next useful evidence will come from independent speed measurements and customer results across real production workloads, including whether low or medium effort can complete routine tasks reliably without extra retries. Artificial Analysis’s launch-day evaluation gives an initial comparison, but it does not settle how the model performs across every type of office, coding or computer-use task.
Teams considering Terra can compare the cost and completion quality of their own tasks at different effort settings, then route harder work to a more capable model where needed. OpenAI has made the model available through its API and listed ChatGPT products; the source material does not specify a later benchmark update or another scheduled release milestone.
Key Questions
What is GPT-6.1 Terra?
GPT-6.1 Terra is a model OpenAI released on October 26, 2026. OpenAI describes it as a fast, efficient option for workplace communication and computer-based tasks.
How much does GPT-6.1 Terra cost?
OpenAI’s listed API price is $1 per million input tokens and $5 per million output tokens, with cached input listed at $0.05 per million tokens. Artificial Analysis measured an average cost of $0.40 per task at maximum effort; that benchmark average is not a fixed charge for every task.
Is Terra OpenAI’s highest-scoring model?
No. Artificial Analysis measured Terra at 48.1 on its Intelligence Index at maximum effort, below GPT-6.1 Sol, GPT-6 Astra and several other models in the supplied comparison.
Which Terra effort setting is the best value?
Artificial Analysis reported that low and medium effort settings were on its cost-efficiency frontier. The best choice for a particular user depends on task difficulty and whether the lower-cost setting completes the work accurately.
Are Terra’s speed and safety claims independently verified?
The supplied material attributes the claim that Terra is more than three times faster than Sol and Astra to OpenAI; it says Artificial Analysis had not published speed measurements at the time. OpenAI’s cybersecurity classification is also its own assessment, not an independent finding in the cited material.
Source: ThorstenMeyerAI.com
