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GLM-5.2 (max)

Z AIGLM오픈 웨이트MIT · 상업적 사용 가능

설명

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.

출시일
2026-06-16
파라미터
753.0B
컨텍스트 길이
1.0M
모달리티
text

능력 레이더

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

랭킹

도메인#순위점수소스
에이전트형 역량34
51.0
LS
코딩 랭킹71
83.0
AA
종합 랭킹31
78.0
AA
과학60
80.0
AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

Agents

Program Bench63.7%자체 보고
Toolathlon48.2%자체 보고
PostTrainBench34.3%자체 보고

Code

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

Math

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

Reasoning

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

AA 평가 지수

(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 카테고리 점수

(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

가격

입력 가격$1.4 / 1M 토큰
출력 가격$4.4 / 1M 토큰
혼합 가격 (3:1)$2.15 / 1M 토큰
캐시 읽기 가격$0.26 / 1M 토큰
캐시 쓰기 가격무료

속도

토큰/초73.8
첫 토큰 지연3.50s
첫 응답 지연30.60s

공급자 가격 순위

공급자 가격 순위

9개 공급자

최저가: DeepInfra최고가: EmpirioLabs AI
공급자입력출력
1DeepInfra최저가
$0
$0
2Fireworks
$0
$0
3ZAI
$0
$0
4Together
$0
$0
5FriendliAI
$0
$0
6Novita
$0
$0
7Z AI주요
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

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