OpenAI Releases GPT-6.1 Terra, Further Improving Cost Efficiency
OpenAI released GPT-6.1 Terra, with input/output prices of $1/$5 per million tokens, lower than GPT-5.6 Terra's $2/$12. On the Artificial Analysis Intelligence Index, at the highest effort level it scores 6 points higher than GPT-5.6 Terra, with a cost per task of $0.40 versus $1.40; at the low and medium effort levels it sits at the frontier of intelligence and cost. On the AA-Omniscience benchmark, the model's guess rate when it does not know the answer dropped from 88% to 38%, while accuracy simultaneously improved by 2 points; Terminal-Bench 4.0 improved by about 20 points, and Coding Agent Index v2.0 scored 48.
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AI score 78
The original text provides specific changes in price, intelligence index, and hallucination rate, allowing readers to judge the new model's position in terms of cost efficiency.
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OpenAI has released GPT-6.1 Terra, pushing the cost efficiency frontier. It is the first Terra-class model since GPT-5.6, and is more intelligent for less than a third of the cost
Pricing per token is half or less that of GPT-5.6 Terra - at $1/$5 per million input/output tokens vs $2/$12 for the previous model. Cache write has also halved, now at $1.25 per million tokens. Cached input is one quarter at $0.05 vs $0.20 per million tokens.
Key takeaways:
➤ Pareto-optimal for Intelligence vs Cost at low and medium effort: At max effort, GPT-6.1 Terra gains 6 points in the Artificial Analysis Intelligence Index over GPT-5.6 Terra, at less than a third of the cost per task ($0.40 vs $1.40). At lower effort levels the gain is larger, between 7 and 13 points. The low and medium effort levels are Pareto-optimal for cost efficiency, while the other effort levels sit behind the frontier. At max effort, the model scores 4 points below GPT-6.1 Sol and 10 points above GPT-6 Luna in the Intelligence Index.
➤ Pushes the Coding Agent Index cost efficiency frontier: With a score of 48 in the newly released Artificial Analysis Coding Agent Index v2.0, the model is 6 points below GPT-6.1 Sol (54) and 17 points above GPT-6 Luna (31). The xhigh and low effort settings sit on the frontier of cost efficiency in the Coding Agent Index, while other effort levels are behind the frontier.
➤ 50 point drop in hallucination rate: GPT-6.1 Terra guesses 38% of the time when it does not know the answer to a question in AA-Omniscience, our private knowledge and hallucination benchmark. Previously, GPT-5.6 Terra's hallucination rate was 88%. This significant reduction in hallucination is coupled with a 2 point increase in AA-Omniscience accuracy - meaning the model simultaneously answers more questions correctly.
➤ 20 point jump in Terminal-Bench 4.0, small improvements across most evaluations: The model makes significant progress in the terminal-based agentic benchmark, Terminal-Bench 4.0, with a gain of ~20 points, now rivaling GPT-6.1 Sol at max effort. Gains across most other evaluations are smaller, for example, 5 points in GDP.pdf.
With a score of 48 in the Artificial Analysis Coding Agent Index v2.0, GPT-6.1 Terra is 6 points below GPT-6.1 Sol (54) and 17 points above GPT-6 Luna (31). The xhigh and low effort settings sit on the frontier of cost efficiency.
GPT-6.1 Terra shows a 50 point drop in hallucination rate, measured in AA-Omniscience. This is coupled with a 2 point increase in AA-Omniscience accuracy - meaning the model simultaneously answers more questions correctly.
The model makes significant progress in the terminal-based agentic benchmark, Terminal-Bench 4.0, with a gain of ~20 points, now rivaling GPT-6.1 Sol at max effort.
Breakdown of the individual evaluations in the Artificial Analysis Intelligence Index v4.3.2
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