GLM-4.7 (Reasoning)
Z AIGLM開源權重MIT · 商用許可
描述
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.
發布日期
2025-12-22
參數規模
358.0B
上下文長度
205K
支援模態
text
能力雷達圖
49
general
61
coding
93
reasoning
60
science
60
agents
0
multimodal
排行榜排名
基準測試分數 (LLM Stats)
(LLM Stats (zeroeval))Agents
Tau-bench
87.4%自報
BrowseCompOpenAI (2025)
52.0%自報
Terminal-Bench 2.0Stanford × Laude Institute (2026)
41.0%自報
Terminal-Bench
33.3%自報
Biology
GPQANYU + Cohere + Anthropic (2023)
85.7%自報
Code
SWE-Bench Verified
73.8%自報
SWE-bench Multilingual
66.7%自報
Finance
MMLU-Pro
84.3%自報
General
LiveCodeBench v6
84.9%自報
Math
AIME 2025
95.7%自報
IMO-AnswerBench
82.0%自報
Humanity's Last Exam
42.8%自報
Reasoning
BrowseComp-zh
66.6%自報
AA 評測指數
(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 分類評分
(LLM Stats (zeroeval))Physics90
Biology90
Chemistry90
Legal80
Math80
Language80
Finance80
Healthcare80
Reasoning70
Frontend Development70
General70
Search60
Tool Calling60
Agents50
Code50
Vision40
定價
輸入價格$0.6 / 1M tokens
輸出價格$2.2 / 1M tokens
混合價格(3:1)$1 / 1M tokens
快取讀取價格$0.11 / 1M tokens
快取寫入價格免費
速度
Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s
供應商價格排行
供應商價格排行
10 個供應商
最便宜: CrofAI最貴: Moark
供應商輸入輸出
1CrofAI最便宜
$0.25
$1.1
2302.AI
$0.286
$1.142
3LLM Gateway
$0.38
$1.98
4DInference
$0.45
$1.65
5Z AI主要
$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
比較該模型在不同 API 供應商之間的定價。