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发现与解读中文优先 · EN 原文AI 模型

Nathan 发布:Long-Horizon Terminal-Bench 评测 Agent 能否完成 300 步以上终端任务

NEW BENCHMARK ON THE @huggingface HUB 您最喜欢的 LLM 代理可以编写脚本。它可以在终端中运行 300 多个步骤而不丢失 THE 图吗?这就是 LONg-HorizON 终端工作台 (LHTB) 测量的内容,46 个任务,cONtaminatiON 抗性,隐藏的验证器检查真实状态,而不是振动。 🏆 排行榜 🥇 @MiniMax_AI 的 Minimax M3 🥈 @Kimi_Moonshot 的 Kimi k2.7 代码 🥉 @Zai_org 的 GLM 5.2 CON 感谢 @zli12321 和团队。超级兴奋看到较小的本地模型如何表现 ON 这个 BENCHMARK @0xSero :)

查看英文原文

NEW BENCHMARK ON THE @huggingface HUB Your favorite LLM agent can write a script. Can it survive 300+ steps in a terminal without losing the plot? That's what Long-Horizon Terminal-Bench (LHTB) measures, 46 tasks, contamination-resistant, hidden verifiers that check real state, not vibes. 🏆 Leaderboard 🥇 @MiniMax_AI 's Minimax M3 🥈 @Kimi_Moonshot 's Kimi k2.7 Code 🥉 @Zai_org's GLM 5.2 Congrats to @zli12321 and team. Super excited to see how smaller local models perf on this benchmark @0xSero :)

NEW BENCHMARK ON THE @huggingface HUB Your favorite LLM agent can write a script. Can it survive 300+ steps in a terminal without losing the plot? That's what Long-Horizon Terminal-Bench (LHTB) measures, 46 tasks, contamination-resistant, hidden verifiers that check real state, not vibes. 🏆 Leaderboard 🥇 @MiniMax_AI 's Minimax M3 🥈 @Kimi_Moonshot 's Kimi k2.7 Code 🥉 @Zai_org's GLM 5.2 Congrats to @zli12321 and team. Super excited to see how smaller local models perf on this benchmark @0xSero :)

评测开始回答‘能撑多久、记多少、是否校准’,而不只是谁的总分更高

为什么值得看

生产 Agent 的上限往往由记忆容量、长链条失败、不确定性和环境反馈共同决定。新评测将判断从单点答案准确率推向系统的可运行边界。

最强反方

2.4 倍验证误差、18% 结合能下降、60% 以上目标改善以及 46 项、300 步等数字来自论文或作者发布;尚无统一基线与跨团队复现。

原始出现与传播对照

1 条出现 · 本次 AIHOT 未精确命中

发现与解读

NEW BENCHMARK ON THE @huggingface HUB 您最喜欢的 LLM 代理可以编写脚本。

NEW BENCHMARK ON THE @huggingface HUB 您最喜欢的 LLM 代理可以编写脚本。它可以在终端中运行 300 多个步骤而不丢失 THE 图吗?这就是 LONg-HorizON 终端工作台 (LHTB) 测量的内容,46 个任务,cONtaminatiON 抗性,隐藏的验证器检查真实状态,而不是振动。 🏆 排行榜 🥇 @MiniMax_AI 的 Minimax M3 🥈 @Kimi_Moonshot 的 Kimi k2.7 代码 🥉 @Zai_org 的 GLM 5.2 CON 感谢 @zli12321 和团队。

查看英文原文

NEW BENCHMARK ON THE @huggingface HUB Your favorite LLM agent can write a script. Can it survive 300+ steps in a terminal without losing the plot? That's what Long-Horizon Terminal-Bench (LHTB) measures, 46 tasks, contamination-resistant, hidden verifiers that check real state, not vibes. 🏆 Leaderboard 🥇 @MiniMax_AI 's Minimax M3 🥈 @Kimi_Moonshot 's Kimi k2.7 Code 🥉 @Zai_org's GLM 5.2 Congrats to @zli12321 and team. Super excited to see how smaller local models perf on this benchmark @0xSero :)

NEW BENCHMARK ON THE @huggingface HUB Your favorite LLM agent can write a script. Can it survive 300+ steps in a terminal without losing the plot? That's what Long-Horizon Terminal-Bench (LHTB) measures, 46 tasks, contamination-resistant, hidden verifiers that check real state, not vibes. 🏆 Leaderboard 🥇 @MiniMax_AI 's Minimax M3 🥈 @Kimi_Moonshot 's Kimi k2.7 Code 🥉 @Zai_org's GLM 5.2 Congrats to @zli12321 and team. Super excited to see how smaller local models perf on this benchmark @0xSero :)

直接发布标题Nathan@nathanhabib1011打开该层出处 ↗

NEW BENCHMARK ON THE @huggingface HUB Your favorite LLM agent can write a script. Can it survive 300+ steps in a terminal without losing the plot? That's what Long-Horizon Terminal-Bench (LHTB) measures, 46 tasks, contamination-resistant, hidden verifiers that check real state, not vibes. 🏆 Leaderboard 🥇 @MiniMax_AI 's Minimax M3 🥈 @Kimi_Moonshot 's Kimi k2.7 Code 🥉 @Zai_org's GLM 5.2 Congrats to @zli12321 and team. Super excited to see how smaller local models perf on this benchmark @0xSero :)

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