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Zai.org发布GLM-5.2长上下文大模型
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新增1M上下文支持和具体性能数据，对比GLM-5.1的30个点提升具有实际应用价值核心解读
Zai_org开源GLM-5.2大模型，提升了长上下文（1M token）能力，在Terminal-Bench 2.1的编码测试中得分提升至81.0（同比提升30个点），引入 henshin分区、Token Stabilizer升级等技术优化，同时保持API定价基本不变，推出多努力级别模型版本
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Z.ai (@Zai_org) 转发了 LMSYS Org (@lmsysorg) 的帖子：
🎉 Meet GLM-5.2 from @Zai_org, the new flagship for long-horizon tasks built on a solid 1M-token context. Day-0 support is now live in SGLang!
✅ Advanced coding capability: 81.0 on Terminal-Bench 2.1 (vs 62.0 for GLM-5.1)
✅ Solid 1M context across long agentic coding trajectories
✅ IndexShare cuts per-token FLOPs by 2.9× at 1M; improved MTP lifts speculative-decoding acceptance by up to 20%
✅ Flexible effort levels (High / Max) for capability vs. latency
Cookbook: https://t.co/tLTYhrAPiI
Run it now with SGLang!
> **引用原帖 Z.ai (@Zai_org):**
> Introducing GLM-5.2: Frontier Intelligence, Open Weights
> - Significant improvements in coding and agentic tasks
> - Strong long-horizon capabilities with a 1M context window
> - Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong balance between performance and token efficiency
> - MIT-licensed open weights
> - Same API pricing as GLM-5.1
> Tech Blog: https://t.co/LAsxUdN0JZ
> Weights: https://t.co/g0A1C4UWx4
> API: https://t.co/Kc3E22cbN7
> Coding Plan: https://t.co/Nk8Y98HNhU
> Chat: https://t.co/WCqWT0qCQb
> https://x.com/Zai_org/status/2066938937344495629