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GLM-5.2 (max)

Z AIGLMOpen WeightMIT · Usage Commercial

Description

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.

Date de sortie
2026-06-16
Paramètres
753.0B
Longueur du contexte
1.0M
Modalités
text

Radar de capacités

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

Classements

Domaine#RangScoreSource
Capacité agentique34
51.0
LS
Classement codage71
83.0
AA
Classement général33
77.0
AA
Science61
79.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

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

Code

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

Math

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

Reasoning

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

Indices d'évaluation AA

(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

Scores par catégorie LLM Stats

(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

Tarification

Prix d'entrée$1.4 / 1M tokens
Prix de sortie$4.4 / 1M tokens
Prix mixte (3:1)$2.15 / 1M tokens
Prix de lecture cache$0.26 / 1M tokens
Prix d'écriture cacheGratuit

Vitesse

Tokens/sec72.6
Délai du premier token7.09s
Temps de réponse34.63s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

9 fournisseurs

Moins cher: DeepInfraPlus cher: EmpirioLabs AI
FournisseurEntréeSortie
1DeepInfraMoins cher
$0
$0
2Together
$0
$0
3FriendliAI
$0
$0
4Novita
$0
$0
5Fireworks
$0
$0
6ZAI
$0
$0
7Z AIPRINCIPAL
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes