GLM-4.7 (Reasoning)
Z AIGLM오픈 웨이트MIT · 상업적 사용 가능
설명
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.
출시일
2025-12-22
파라미터
358.0B
컨텍스트 길이
205K
모달리티
text
능력 레이더
49
general
61
coding
93
reasoning
60
science
60
agents
0
multimodal
랭킹
벤치마크 점수 (LLM Stats)
(LLM Stats (zeroeval))Agents
Tau-bench
87.4%자체 보고
BrowseCompOpenAI (2025)
52.0%자체 보고
Terminal-Bench 2.0Stanford × Laude Institute (2026)
41.0%자체 보고
Terminal-Bench
33.3%자체 보고
Biology
GPQANYU + Cohere + Anthropic (2023)
85.7%자체 보고
Code
SWE-Bench Verified
73.8%자체 보고
SWE-bench Multilingual
66.7%자체 보고
Finance
MMLU-Pro
84.3%자체 보고
General
LiveCodeBench v6
84.9%자체 보고
Math
AIME 2025
95.7%자체 보고
IMO-AnswerBench
82.0%자체 보고
Humanity's Last Exam
42.8%자체 보고
Reasoning
BrowseComp-zh
66.6%자체 보고
AA 평가 지수
(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 10.5
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 Banking0.1
LLM Stats 카테고리 점수
(LLM Stats (zeroeval))Physics90
Biology90
Chemistry90
Legal80
Math80
Language80
Finance80
Healthcare80
Reasoning70
Frontend Development70
General70
Search60
Tool Calling60
Agents50
Code50
Vision40
가격
입력 가격$0.6 / 1M 토큰
출력 가격$2.2 / 1M 토큰
혼합 가격 (3:1)$1 / 1M 토큰
캐시 읽기 가격$0.11 / 1M 토큰
캐시 쓰기 가격무료
속도
토큰/초0.0
첫 토큰 지연0.00s
첫 응답 지연0.00s
공급자 가격 순위
공급자 가격 순위
1개 공급자
공급자입력출력
1Z AI주요
$0.6
$2.2
이 모델의 다양한 API 공급자 간 가격 비교.