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GLM-4.7 (Reasoning)

Z AIGLMOpen WeightMIT · Usage Commercial

Description

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.

Date de sortie
2025-12-22
Paramètres
358.0B
Longueur du contexte
205K
Modalités
text

Radar de capacités

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

Classements

Domaine#RangScoreSource
Capacité agentique87
42.0
LS
Classement codage121
69.0
AA
Classement général70
76.0
AA
Science96
71.0
AA

Scores 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.

Indices d'évaluation 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

Scores par catégorie 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

Tarification

Prix d'entrée$0.6 / 1M tokens
Prix de sortie$2.2 / 1M tokens
Prix mixte (3:1)$1 / 1M tokens
Prix de lecture cache$0.11 / 1M tokens
Prix d'écriture cacheGratuit

Vitesse

Tokens/sec0.0
Délai du premier token0.00s
Temps de réponse0.00s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

10 fournisseurs

Moins cher: CrofAIPlus cher: Moark
FournisseurEntréeSortie
1CrofAIMoins cher
$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

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes

LLM StatsArtificial Analysis