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GLM-5.2 (max)

Z AIGLM开源权重MIT · 商用许可

描述

GLM-5.2 is Z.AI's flagship foundation model built for long-horizon tasks, delivering a solid 1M-token context that stably sustains long, messy coding-agent trajectories. It improves substantially over GLM-5.1, becoming the strongest open-source model on standard coding benchmarks (81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro) and the highest-ranked open-source model across long-horizon coding benchmarks (FrontierSWE, PostTrainBench, SWE-Marathon). It introduces flexible thinking effort levels (High and Max) to balance capability against latency and compute. Architecturally, GLM-5.2 proposes IndexShare, which reuses one lightweight indexer across every four sparse-attention (DSA) layers to cut per-token FLOPs by 2.9x at 1M context, and an improved MTP layer for speculative decoding that raises acceptance length by up to 20%. Released under a pure MIT open-source license with weights available on HuggingFace and ModelScope, it supports transformers, vLLM, SGLang, xLLM, and ktransformers, with 1M input context, 128K max output, thinking mode, function calling, structured output, context caching, and MCP integration.

发布日期
2026-06-16
参数规模
753.0B
上下文长度
1.0M
支持模态
text

能力雷达图

36
general
66
coding
90
reasoning
66
science
70
agents
0
multimodal

排行榜排名

领域#排名分数来源
智能体能力模型榜34
51.0
LS
代码能力榜72
83.0
AA
通用能力榜32
78.0
AA
科学能力61
80.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Agents

Program Bench63.7%自报
Toolathlon48.2%自报
PostTrainBench34.3%自报

Code

FrontierSWE74.0%
NL2Repo48.9%自报
DeepSWE46.2%自报
DeepSWE 1.144.0%
SWE-Marathon13.0%自报

Math

AIME 202699.2%自报
HMMT 202594.4%自报
HMMT Feb 2692.5%自报
IMO-AnswerBench91.0%自报

Reasoning

GPQANYU + Cohere + Anthropic (2023)91.2%自报
Terminal-Bench 2.182.7%自报
MCP Atlas76.8%自报
SWE-Bench ProPrinceton NLP (2024)62.1%自报
Humanity's Last Exam54.7%自报
FrontierCode 1.124.5%
CritPT16.7%自报

AA 评测指数

(Artificial Analysis)
Tau2(Sierra + U Toronto + Vector Institute (2025))
99.1
Gpqa(NYU + Cohere + Anthropic (2023))
89.5
Lcr(Artificial Analysis)
78.3
Terminalbench V2 1
77.9
Ifbench(Google Research (2023))
73.3
Coding Index(Artificial Analysis)
68.8
Scicode(UIUC + Argonne National Lab (2024))
51.2
Terminalbench Hard(Stanford × Laude Institute (2026))
50.8
Hle(Center for AI Safety + Scale AI (2025))
41.1
Tau Banking
34.6
Intelligence Index(Artificial Analysis)
34.0

LLM Stats 分类评分

(LLM Stats (zeroeval))
Physics
90
Biology
90
Chemistry
90
Math
70
Tool Calling
70
Reasoning
60
General
60
Agents
50
Code
50
Vision
50
Systems
30

定价

输入价格$1.4 / 1M tokens
输出价格$4.4 / 1M tokens
混合价格(3:1)$2.15 / 1M tokens
缓存读取价格$0.26 / 1M tokens
缓存写入价格免费

速度

Tokens/秒77.3
首Token延迟6.97s
首回答延迟32.85s

供应商价格排行

供应商价格排行

9 个供应商

最便宜: DeepInfra最贵: EmpirioLabs AI
供应商输入输出
1DeepInfra最便宜
$0
$0
2ZAI
$0
$0
3Fireworks
$0
$0
4FriendliAI
$0
$0
5Together
$0
$0
6Novita
$0
$0
7Z AI主要
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

比较该模型在不同 API 供应商之间的定价。

外部链接