# GLM-5.2 成为 Artificial Analysis 智能指数领先开放权重模型

- 来源：Hacker News 热门（buzzing.cc 中文翻译）
- 作者：himata4113
- 发布时间：2026-06-17 19:09
- AIHOT 分数：57
- AIHOT 链接：https://aihot.virxact.com/items/cmqhzl8eo047kslf0psa3uqyw
- 原文链接：https://artificialanalysis.ai/articles/glm-5-2-is-the-new-leading-open-weights-model-on-the-artificial-analysis-intelligence-index

## AI 摘要

GLM-5.2 在 Artificial Analysis Intelligence Index v4.1 上得分 51，领先 MiniMax-M3（44）、DeepSeek V4 Pro（max，44）和 Kimi K2.6（43）。模型总参数 744B，活跃参数 40B，上下文窗口 1M tokens，API 定价每百万输入/输出/缓存命中 token 分别为 $1.4/$4.4/$0.26。科学推理显著提升：HLE 得分 40%（+12）、CritPt 21%（+16）。GDPval-AA v2 得分 1524，与 GPT-5.5（xhigh）持平。每任务输出 43k tokens（其中 37k 推理），每任务成本约 $0.46，位于智能 vs 成本帕累托前沿。采用 MIT 许可证，可通过 DeepInfra、Novita 等第三方平台使用。

## 正文

Artificial Analysis

All articles

June 17, 2026

GLM-5.2 is the new leading open weights model on the Artificial Analysis Intelligence Index

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

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)

Additional Model Details:

➤ License: MIT

➤ Size: 744B total parameters, 40B active parameters, equivalent to GLM-5.1

➤ Context window: 1M tokens, up from 200K on GLM-5.1

➤ Pricing: $1.4/$0.26/$4.4 per 1M input/cache hit/output tokens

➤ Availability: Alongside Z ai's first-party API, GLM-5.2 is available across third-party providers including DeepInfra, Novita, Nebius, Parasail, Siliconflow, GMI Cloud, Baseten, and Fireworks

GLM-5.2 leads all open weights models on GDPval-AA v2, our primary metric for real-world agentic performance. At 1524 it places ahead of MiniMax-M3 (1418) and DeepSeek V4 Pro (max, 1328), and is effectively level with GPT-5.5 (xhigh, 1514). We visually inspected GLM-5.2's outputs across a range of GDPval-AA tasks. We have attached a selection below.

GLM-5.2 scores 4 on the AA-Omniscience Index, up from GLM-5.1 (2). The gain comes from both higher accuracy (25.1% vs 24.2%) and a lower hallucination rate (28.1% vs 29.4%), with attempt rate flat at 47%.

GLM-5.2 uses 43k output tokens per Intelligence Index task, of which 37k is reasoning. This is up from GLM-5.1 (26k) and higher than open weights peers MiniMax-M3 (24k) and Kimi K2.6 (35k), placing it among the less token-efficient open weights models at its intelligence level. GLM-5.2 sits off the most attractive quadrant on the Intelligence vs Output Tokens chart.

Breakdown of the individual evaluations in the Artificial Analysis Intelligence Index v4.1.

Compare GLM-5.2 with other leading models at: https://artificialanalysis.ai/models/glm-5-2

Read the latest

Artificial Analysis Intelligence Index v4.1: a shift toward agentic workloads

Announcing Artificial Analysis Intelligence Index v4.1: a shift toward agentic workloads, featuring upgraded benchmarks and new per-task metrics

June 16, 2026

Claude Fable 5 Launches at #1 on the Artificial Analysis Intelligence Index

Anthropic is nearly 5 points ahead of any other lab’s best model

June 10, 2026

Claude Fable 5: the first public Mythos-class model

Anthropic has released Claude Fable 5, the first publicly available Mythos-class model that ranks #1 in our agentic real-world knowledge work benchmark GDPval-AA

June 9, 2026