Kim指出,GLM 5.2是首个能以开放权重处理真实自动研究任务的模型,包括调试设置、跨多节点H100集群运行并比较RL训练实验。其局限在于缺少图像理解能力,需程序化分析原始WandB数据而非可视化图表。引用介绍称,GLM 5.2是其自动研究pipeline上首个能胜任实际研究的开源模型,在Fable 5对研究设限的背景下意义重大。演示中,它基于SkyRL在两台8×H100节点上完成Harbour代码竞赛的完全异步vs同位置同步RL训练,自动解决设置问题并生成吞吐量与奖励稳定性对比。
GLM 5.2 keeps on winning
GLM 5.2 is emerging as the first open-weights model capable of handling meaningful autoresearch tasks, from debugging setup issues to running and comparing RL training experiments across multi-node H100 clusters.
The big caveat: it lacks image understanding, so unlike Opus or Fable, it has to analyze raw WandB data programmatically rather than visually interpreting charts.
Still: while we are waiting for the come back of. Fable 5, zAI really nailed it with GLM 5.2