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GLM-4.7 (Reasoning)

Z AIGLMOpen WeightMIT · Uso Comercial

Descripción

GLM 4.7 is a coding‑centric model that thinks before acting, preserves its reasoning across turns, and lets you control thinking per request for speed or accuracy. It upgrades agentic workflows with stronger multi‑step tool use, better terminal and multilingual coding, and a noticeable jump in UI output quality for modern, clean webpages and slides. You can use it in popular coding agents, call it via the Z.ai API, and even run it locally with public weights on HuggingFace and ModelScope using vLLM or SGLang.

Fecha de lanzamiento
2025-12-22
Parámetros
358.0B
Longitud del contexto
205K
Modalidades
text

Radar de capacidades

49
general
61
coding
93
reasoning
60
science
60
agents
0
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica87
42.0
LS
Ranking de codificación121
69.0
AA
Ranking general70
76.0
AA
Ciencia96
71.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

Tau-bench87.4%Aut.
BrowseCompOpenAI (2025)52.0%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)41.0%Aut.
Terminal-Bench33.3%Aut.

Biology

GPQANYU + Cohere + Anthropic (2023)85.7%Aut.

Code

SWE-Bench Verified73.8%Aut.
SWE-bench Multilingual66.7%Aut.

Finance

MMLU-Pro84.3%Aut.

General

LiveCodeBench v684.9%Aut.

Math

AIME 202595.7%Aut.
IMO-AnswerBench82.0%Aut.
Humanity's Last Exam42.8%Aut.

Reasoning

BrowseComp-zh66.6%Aut.

Índices de evaluación AA

(Artificial Analysis)
Math Index(Artificial Analysis)
95.0
Coding Index(Artificial Analysis)
45.3
Intelligence Index(Artificial Analysis)
34.5
Tau2(Sierra + U Toronto + Vector Institute (2025))
1.0
Aime 25(MAA (Mathematical Association of America))
0.9
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.9
Gpqa(NYU + Cohere + Anthropic (2023))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.9
Lcr(Artificial Analysis)
0.7
Ifbench(Google Research (2023))
0.7
Terminalbench V2 1
0.5
Scicode(UIUC + Argonne National Lab (2024))
0.5
Terminalbench Hard(Stanford × Laude Institute (2026))
0.3
Hle(Center for AI Safety + Scale AI (2025))
0.3
Tau Banking
0.1

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Physics
90
Biology
90
Chemistry
90
Legal
80
Math
80
Language
80
Finance
80
Healthcare
80
Reasoning
70
Frontend Development
70
General
70
Search
60
Tool Calling
60
Agents
50
Code
50
Vision
40

Precios

Precio de entrada$0.6 / 1M tokens
Precio de salida$2.2 / 1M tokens
Precio mixto (3:1)$1 / 1M tokens
Precio de lectura caché$0.11 / 1M tokens
Precio de escritura cachéGratis

Velocidad

Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

10 proveedores

Más barato: CrofAIMás caro: Moark
ProveedorEntradaSalida
1CrofAIMás barato
$0.25
$1.1
2302.AI
$0.286
$1.142
3LLM Gateway
$0.38
$1.98
4DInference
$0.45
$1.65
5Z AIPRINCIPAL
$0.6
$2.2
6Z.AI
$0.6
$2.2
7OpenCode Zen
$0.6
$2.2
8Zhipu AI
$0.6
$2.2
9Cortecs
$0.78
$2.785
10Moark
$3.5
$14

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas

LLM StatsArtificial Analysis