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
42
general
62
coding
93
reasoning
68
science
60
agents
0
multimodal
랭킹
벤치마크 점수 (LLM Stats)
(LLM Stats (zeroeval))General
Tau-bench
87.4%자체 보고
Language
MMLU-Pro
84.3%자체 보고
Math
AIME 2025
95.7%자체 보고
IMO-AnswerBench
82.0%자체 보고
Reasoning
GPQANYU + Cohere + Anthropic (2023)
85.7%자체 보고
LiveCodeBench v6
84.9%자체 보고
SWE-Bench Verified
73.8%자체 보고
SWE-bench Multilingual
66.7%자체 보고
BrowseComp-zh
66.6%자체 보고
BrowseCompOpenAI (2025)
52.0%자체 보고
Humanity's Last Exam
42.8%자체 보고
Terminal-Bench 2.0Stanford × Laude Institute (2026)
41.0%자체 보고
Terminal-Bench
33.3%자체 보고
AA 평가 지수
(Artificial Analysis)Tau2(Sierra + U Toronto + Vector Institute (2025))95.9
Math Index(Artificial Analysis)95.0
Aime 25(MAA (Mathematical Association of America))95.0
Livecodebench(UC Berkeley + MIT + Cornell (2024))89.4
Gpqa(NYU + Cohere + Anthropic (2023))85.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))85.6
Lcr(Artificial Analysis)71.0
Ifbench(Google Research (2023))67.9
Terminalbench V2 145.3
Coding Index(Artificial Analysis)45.3
Terminalbench Hard(Stanford × Laude Institute (2026))31.8
Hle(Center for AI Safety + Scale AI (2025))27.4
Intelligence Index(Artificial Analysis)22.2
Tau Banking12.2
LLM Stats 카테고리 점수
(LLM Stats (zeroeval))Physics90
Biology90
Chemistry90
Language80
Legal80
Math80
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
2개 공급자
최저가: DeepInfra최고가: Z AI
공급자입력출력
1DeepInfra최저가
$0
$0
2Z AI주요
$0.6
$2.2
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