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GLM-4.5-Air

Z AIGLM開源權重MIT · 商用許可

描述

GLM-4.5-Air is a more compact variant of GLM-4.5 designed for efficient Agentic, Reasoning, and Coding (ARC) applications. It features 106 billion total parameters with 12 billion active parameters using MoE architecture. Like GLM-4.5, it is a hybrid reasoning model providing thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses. Despite its compact design, GLM-4.5-Air delivers competitive performance with a score of 59.8 across 12 industry-standard benchmarks, ranking 6th overall while maintaining superior efficiency. It supports 128K context length and is released under MIT open-source license allowing commercial use.

發布日期
2025-07-28
參數規模
106.0B
上下文長度
131K
支援模態
text

能力雷達圖

35
general
60
coding
79
reasoning
45
science
70
agents
0
multimodal

排行榜排名

領域#排名分數來源
智慧體能力模型榜86
42.0
LS
程式碼能力榜203
54.0
AA
通用能力榜291
45.0
AA
科學能力292
46.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

BFCL-v376.4%自報
Terminal-Bench30.0%自報
BrowseCompOpenAI (2025)21.3%自報

Biology

GPQANYU + Cohere + Anthropic (2023)75.0%自報
SciCode37.3%自報

Code

LiveCodeBench70.7%自報
SWE-Bench Verified57.6%自報

Communication

TAU-bench Retail77.9%自報
TAU-bench Airline60.8%自報

Finance

MMLU-Pro81.4%自報

General

AA-Index64.8%自報

Math

MATH-50098.1%自報
AIME 202489.4%自報
Humanity's Last Exam10.6%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
80.7
Intelligence Index(Artificial Analysis)
16.7
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
1.0
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Aime 25(MAA (Mathematical Association of America))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.7
Aime(MAA (Mathematical Association of America))
0.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.5
Lcr(Artificial Analysis)
0.5
Ifbench(Google Research (2023))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.3
Terminalbench Hard(Stanford × Laude Institute (2026))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.1

LLM Stats 分類評分

(LLM Stats (zeroeval))
Legal
80
Structured Output
80
Language
80
Finance
80
Healthcare
80
Communication
70
Tool Calling
70
Math
60
Physics
60
Reasoning
60
Frontend Development
60
General
60
Biology
60
Chemistry
60
Code
50
Agents
40
Search
20
Vision
10

定價

輸入價格$0.17 / 1M tokens
輸出價格$0.98 / 1M tokens
混合價格(3:1)$0.372 / 1M tokens
快取讀取價格$0.03 / 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

9 個供應商

最便宜: ZenMux最貴: OrcaRouter
供應商輸入輸出
1ZenMux最便宜
$0.11
$0.56
2302.AI
$0.1143
$0.286
3OpenRouter
$0.13
$0.85
4Kilo Gateway
$0.13
$0.85
5LLM Gateway
$0.13
$0.85
6Z AI主要
$0.17
$0.98
7Z.AI
$0.2
$1.1
8Zhipu AI
$0.2
$1.1
9OrcaRouter
$0.2
$1.1

比較該模型在不同 API 供應商之間的定價。

外部連結