Artificial Analysis@ArtificialAnlys

2026-06-17 14:41·15天前

AI 摘要

Z ai 发布 GLM-5.2（744B 总参数/40B 活跃参数），在 Artificial Analysis Intelligence Index v4.1 上得分 51，超越 MiniMax-M3、DeepSeek V4 Pro 和 Kimi K2.6。科学推理大幅提升：CritPt +16、HLE +12、GPQA Diamond 达 89%。GDPval-AA v2 得分 1524，与 GPT-5.5 (xhigh reasoning) 相当。上下文窗口扩展至 1M tokens，MIT 许可证。第一方 API 定价 $1.4/$4.4/$0.26 每百万输入/输出/缓存命中 token，每任务成本约 $0.46，处于智能 vs 成本帕累托前沿。

Z ai's GLM-5.2 is the new leading open weights model on the Artificial Analysis Intelligence Index scoring 51 and it sits on the Pareto frontier of Intelligence vs Cost per Task

@Zai_org's GLM-5.2 is the same size as GLM-5.1 （744B total / 40B active parameters） but scores 11 points higher on the Intelligence Index v4.1， placing ahead of MiniMax-M3 （44） and DeepSeek V4 Pro （max， 44）. On the first-party API it is priced in line with GLM-5.1 at $1.4/$4.4/$0.26 per 1M input/output/cache hit tokens

Key results：

➤ GLM-5.2 is the leading open weights model on the Intelligence Index v4.1. At 51， it leads MiniMax-M3 （44）， DeepSeek V4 Pro （max， 44） and Kimi K2.6 （43）

➤ Improvements across most evaluations， particularly scientific reasoning： GLM-5.2 gains over GLM-5.1 on most evaluations， led by scientific reasoning on CritPt （+16 points to 21%） and HLE （+12 points to 40%）， alongside AA-LCR （+9 points to 71%）， tau3 banking （+15 points to 27%） and SciCode （+7 points to 50%）. TerminalBench v2.1 also improves （+16 points to 78%） and GPQA Diamond gains 3 points to 89%

➤ Leading open weights model on GDPval-AA v2 and competitive with proprietary models： GLM-5.2 scores 1524 on GDPval-AA v2， ahead of MiniMax-M3 （1418） and DeepSeek V4 Pro （max， 1328）. This impressive result places GLM-5.2 in-line with proprietary models including GPT-5.5 （xhigh reasoning）. GDPval-AA v2 builds on the original GDPval-AA by baselining Elo to human performance at 1000， introducing a rotating panel of frontier-model judges， and raising the turn limit from 100 to 250 for longer-horizon agent trajectories

➤ GLM-5.2 uses more output tokens per task than other leading open weights models： the model uses 43k output tokens per Intelligence Index task， up from GLM-5.1 （26k） and above MiniMax-M3 （24k）， Kimi K2.6 （35k） and DeepSeek V4 Pro （max， 37k）

➤ On the Intelligence vs. Cost per Task Pareto Frontier： GLM-5.2 is on the Pareto frontier of the Intelligence vs Cost per Task chart， with the lowest cost per task among models at its intelligence level. GLM-5.2 costs ~$0.46 per task， compared to GLM-5.1 （$0.25）， Kimi K2.6 （$0.31）， MiniMax-M3 （$0.18） and DeepSeek V4 Pro （max， $0.05）

Artificial Analysis@ArtificialAnlys · X

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2026-06-17 14:41·15天前

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AI 摘要

Z ai's GLM-5.2 is the new leading open weights model on the Artificial Analysis Intelligence Index scoring 51 and it sits on the Pareto frontier of Intelligence vs Cost per Task