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GPT-6.1 Terra大幅降低了OpenAI相关API的定价,并且在处理更大型模型方面依然表现出色。

原文标题 · GPT-6.1 Terra halves OpenAI's API prices and still gains ground on its larger models

OpenAI发布了GPT-6.1 Terra这一中端模型。与之前的版本相比,该模型的API价格降低了一半。分析人士认为,这一模型在每美元智能价值方面树立了新的标准,尤其适用于日常计算任务以及由人工智能驱动的计算机控制领域。这篇报道《GPT-6.1 Terra将OpenAI的API价格降低了一半,同时仍优于其更大型的模型》最初发表于The Decoder网站上。

来源:The Decoder · the-decoder.com

正文为英文,可一键机器翻译(仅首次需要等待)

GPT-6.1 Terra halves OpenAI's API prices and still gains ground on its larger models

Key Points

OpenAI has released GPT-6.1 Terra, a new mid-range AI model at half the API price of its predecessor.

OpenAI built the model for office tasks and automated software control.

Benchmarks show a sharply better price-to-performance ratio and fewer hallucinations.

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. Ad

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. Ad

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. Ad

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. Ad

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. Ad

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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