# Long-Horizon-Terminal-Bench 2.0: Automating Diverse Task Construction and Measuring Sustained Agent Progress

Published: 2026-10-14 · Updated: 2026-10-14 · Category: Benchmark

Source page: https://www.sipply.dev/story/long-horizon-terminal-bench-2-0-automating-diverse-task-f90a5ec7 · 中文: https://www.sipply.dev/zh/story/long-horizon-terminal-bench-2-0-automating-diverse-task-f90a5ec7

## Summary

The Long-Horizon-Terminal-Bench 2.0 (LHTB 2.0) has been introduced as an advanced framework for evaluating the performance of AI agents on extended tasks. This updated benchmark addresses previous limitations by expanding the range of tasks to 77, covering diverse domains. A key feature of LHTB 2.0 is its focus on measuring sustained progress and intermediate achievements, rather than solely concentrating on final outcomes, which provides a more comprehensive assessment of an agent's capabilities over time.

## Key takeaways

- LHTB 2.0 expands the task range to 77, enhancing evaluation diversity.
- The benchmark emphasizes sustained progress, offering a more nuanced view of AI performance.
- It aims to correct previous issues in evaluating long-horizon tasks.

## Why it matters

This benchmark is significant as it sets a new standard for evaluating AI agents, encouraging the development of systems that can sustain performance over time rather than just achieving end goals.

- **Product managers:** For product managers, understanding LHTB 2.0 can inform the development of AI products that prioritize sustained user engagement and performance, aligning with market needs for reliable and effective AI solutions.
- **Developers:** Developers and engineers can leverage LHTB 2.0 to design AI systems that are evaluated on their ability to maintain progress over long tasks, fostering innovation in task-oriented AI applications.
- **Students and job seekers:** Students and job-seekers in AI can benefit from familiarizing themselves with LHTB 2.0, as it represents a cutting-edge approach to performance evaluation that may influence future research and job opportunities in the field.

## Sources

- [Long-Horizon-Terminal-Bench 2.0: Automating Diverse Task Construction and Measuring Sustained Agent Progress](https://arxiv.org/abs/2610.14146) (arXiv cs.AI, 2026-10-14)

## 中文

### 长远终端基准 2.0：自动化多样化任务构建与持续代理进展测量

长远终端基准 2.0 (LHTB 2.0) 被引入作为评估 AI 代理在扩展任务上表现的先进框架。此更新的基准通过将任务范围扩展到 77 个，涵盖多样化领域，解决了之前的局限性。LHTB 2.0 的一个关键特性是其关注持续进展和中间成就的测量，而不仅仅集中于最终结果，这为评估代理的能力提供了更全面的视角。

**要点：**

- LHTB 2.0 将任务范围扩展到 77 个，增强了评估的多样性。
- 该基准强调持续进展，提供了对 AI 性能的更细致视角。
- 旨在纠正评估长远任务中的先前问题。

**为什么重要：** 该基准具有重要意义，因为它为评估 AI 代理设定了新标准，鼓励开发能够持续表现的系统，而不仅仅是实现最终目标。

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