GPT-6.1 Terra将OpenAI的API价格减半，并仍在更大的模型上取得进展
关键点
- OpenAI拥有发布 GPT-6.1 Terra，是一种新的中程AI模型，其前身的API价格为一半。
- OpenAI为办公室任务和自动化软件控制建立了模型。
- 基准测试显示价格与性能之比明显改善，幻觉减少。
OpenAI拥有发布 GPT-6.1 Terra，这个模型它称将成本对性能边界推得比任何前身都远。 API的价格是GPT-5.6 Terra的一半。
Terra是OpenAI最接近Anthropic中层索内系列的竞争对手，价格为一半。 投入令牌每百万美元花费1美元，产出令牌5美元，而Claude Sonnet 5.5美元花费2美元和10美元，GPT-5.6 Terra则花费2美元和12美元。 缓存投入下降到每百万令牌只有0.5美元，是先前的四分之一。
OpenAI认为，该模型将快速视觉推理与精确的计算机控制以及更自然的写作风格相结合，以日常的工作任务为目标，从起草提案到解释技术图纸到填表。 GPT-6.1 Terra现在可供Plus, Pro, Entertainment，以及ChatGPT Work和Codex中的Edu用户使用，并通过API.
分析员说，成本效率达到了新的高点
人工分析将GPT-6.1 Terra称为新的基准测试，用于每美元的情报。 在最大推理努力中，模型在情报指数上比GPT-5.6 Terra获得6分，而每个任务的成本不到三分之一(0.40美元对1.4美元)。 在较低的努力水平上，收益甚至更大——7至13点——将模型放在帕雷托边疆，而成本和绩效都不能再同时提高。
在新的Coding Agent Index v2.0中，Terra得分48分，GPT-6.1 Sol(54)以下6分，GPT-6 Luna(31)以上17分。 幻觉的下降更大在私人的AA-Omniscience 基准测试上，模型在缺乏答案时只能猜测38%的时间，低于GPT-5.6 Terra的88%. 准确性也上升了两点。
计算机控制比最大的模型快三倍
OpenAI定位为GPT-6.1 Terra在自动化软件控制方面特别强大。 在Agents的"最后的考试"基准测试上，它与GPT-6 Astra的性能相匹配，其比价为象征性价格的十分之一。 与最大努力的Claude Opus 5.5相比，Terra以1/4的标价，超过3倍的象征效率。 也就是说，每项任务的费用大约为9倍。 它还比GPT-6 Astra和GPT-6.1 Sol公司称的完成速度快三倍以上。
在MMMU-Pro用于视觉推理上，GPT-6.1 Terra在每一个推理级别上都超过了它的前身，几乎与GPT-6 Astra和GPT-6.1 Sol匹配。 在桌面agent 基准测试 OSWorld 2.1上，它击败了GPT-5.6. Terra在中度努力下取得最佳成绩成本的一小部分。
Terra 也是显示编码的急剧改进。 在Bench 4.0,GPT-6.1号航站楼 Terra在最大推理努力中解决了50.3%的任务，比GPT-5.6 Terra的21.5%有所上升。 根据人工分析，20分跳跃将模型置于GPT-6.1 Sol的同一层。 在科学编码基准测试终端-Bench-Science 0.1上，Terra超越了GPT-6. 以较低的成本溶解，并进入Claude Opus 5.5的五点以低于估计费用的五分之一。 然而对于要求最高的编码任务，OpenAI仍然推荐GPT-6.1 Sol和GPT-6 Astra.
Terra属于OpenAI的安全门槛
GPT-6.1 Terra满足OpenAI公司"备战框架"确定的"关键"网络安全门槛，继承了GPT-6 Astra的保障措施。 与其前身相比，该模型更有可能停留在指定范围内，并向用户披露限制。
根据系统卡，GPT-6.1 Terra与GPT-6 Astra和GPT-6.1 Sol一样，防止直接攻击教学层级，这些模型在这类测试中达到99.99%。 对于间接的提示词注入攻击，如果恶意指令被埋藏在第三方内容中，Terra的防御率是98.8%，而与GPT-5.6 Terra的防御率为96.2%.
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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.
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.
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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