跳轉到主要內容

GLM-5.2 (max)

Z AIGLM開源權重MIT · 商用許可

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.

發布日期
2026-06-16
參數規模
753.0B
上下文長度
1.0M
支援模態
text

能力雷達圖

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

排行榜排名

領域#排名分數來源
智慧體能力模型榜34
51.0
LS
程式碼能力榜71
83.0
AA
通用能力榜31
78.0
AA
科學能力60
80.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

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

Code

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

Math

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

Reasoning

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

AA 評測指數

(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 分類評分

(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

定價

輸入價格$1.4 / 1M tokens
輸出價格$4.4 / 1M tokens
混合價格(3:1)$2.15 / 1M tokens
快取讀取價格$0.26 / 1M tokens
快取寫入價格免費

速度

Tokens/秒78.1
首Token延遲6.82s
首回答延遲32.44s

供應商價格排行

供應商價格排行

9 個供應商

最便宜: DeepInfra最貴: EmpirioLabs AI
供應商輸入輸出
1DeepInfra最便宜
$0
$0
2FriendliAI
$0
$0
3ZAI
$0
$0
4Novita
$0
$0
5Together
$0
$0
6Fireworks
$0
$0
7Z AI主要
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

比較該模型在不同 API 供應商之間的定價。

外部連結