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GLM-5.2 (max)

Z AIGLMOpen WeightMIT · Uso Comercial

Descripción

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.

Fecha de lanzamiento
2026-06-16
Parámetros
753.0B
Longitud del contexto
1.0M
Modalidades
text

Radar de capacidades

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

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica34
51.0
LS
Ranking de codificación71
83.0
AA
Ranking general33
77.0
AA
Ciencia61
79.0
AA

Puntuaciones 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.

Índices de evaluación 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

Puntuaciones por categoría 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

Precios

Precio de entrada$1.4 / 1M tokens
Precio de salida$4.4 / 1M tokens
Precio mixto (3:1)$2.15 / 1M tokens
Precio de lectura caché$0.26 / 1M tokens
Precio de escritura cachéGratis

Velocidad

Tokens/seg72.3
Retraso del primer token7.18s
Tiempo hasta la respuesta34.84s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

9 proveedores

Más barato: DeepInfraMás caro: EmpirioLabs AI
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2Fireworks
$0
$0
3ZAI
$0
$0
4Novita
$0
$0
5FriendliAI
$0
$0
6Together
$0
$0
7Z AIPRINCIPAL
$1.4
$4.4
8Neon
$1.4
$4.4
9EmpirioLabs AI
$1.4
$4.4

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas