GLM 5.2
GLM 5.2 是智谱(Z.ai)推出的大规模推理模型,支持文本输入输出,拥有 100 万 token 上下文窗口,适用于长周期 Agent 工作流、工程级软件开发等场景。
模态
上下文
1.05Mtokens
最大输出 944K tokens
排名与分数走势
排名
净改善度
能力
工具调用 (Tools)
结构化输出
并行工具调用
视觉输入
音频输入
多服务商价格对比数据来自 OpenRouter
| 服务商 | 量化精度 | 上下文 | 输入/M | 输出/M | 缓存读取/M | 近1天可用率 |
|---|---|---|---|---|---|---|
W Wafer | fp4 | 1.05M | ¥0.23 | ¥46.89 | ¥0.22 | 100.0% |
| fp8 | 1.05M | ¥0.53 | ¥40.19 | ¥0.53 | 99.8% | |
| fp8 | 1.05M | ¥1.27 | ¥3.98 | ¥0.24 | 100.0% | |
| — | 262K | ¥1.27 | ¥53.59 | ¥1.27 | 100.0% | |
W Wafer | fp4 | 1.05M | ¥1.27 | ¥66.98 | ¥1.21 | 100.0% |
| — | 1.05M | ¥2.68 | ¥26.79 | ¥0.54 | 99.9% | |
| fp4 | 1.05M | ¥3.01 | ¥9.65 | ¥0.56 | 94.8% | |
| fp8 | 1.02M | ¥3.72 | ¥11.69 | ¥0.69 | 99.9% | |
| fp4 | 1.05M | ¥3.77 | ¥12.06 | ¥0.70 | 100.0% | |
C CoreWeave | fp4 | 1.05M | ¥4.15 | ¥16.21 | ¥0.94 | 97.1% |
| fp8 | 1.05M | ¥4.35 | ¥13.68 | ¥0.81 | 100.0% | |
I Inceptron | fp4 | 1.05M | ¥4.62 | ¥6.96 | ¥0.94 | 99.3% |
| — | 1.05M | ¥4.69 | ¥14.74 | ¥0.70 | 100.0% | |
S SiliconFlow限时 -50% | fp8 | 1.05M | ¥4.69 | ¥14.74 | ¥0.87 | 99.8% |
| fp8 | 1.05M | ¥6.28 | ¥19.75 | ¥1.17 | 100.0% | |
| fp8 | 1.00M | ¥6.47 | ¥20.34 | ¥1.29 | 98.1% | |
| fp8 | 1.00M | ¥7.50 | ¥23.58 | ¥1.50 | 100.0% | |
P Phala | fp8 | 1.05M | ¥8.44 | ¥20.10 | ¥1.47 | 23.5% |
| fp4 | 1.05M | ¥9.38 | ¥29.47 | - | 95.6% | |
| nvfp4 | 1.05M | ¥9.38 | ¥29.47 | ¥0.94 | 99.9% | |
| fp8 | 1.05M | ¥9.38 | ¥29.47 | ¥0.94 | 100.0% | |
| — | 1.05M | ¥9.38 | ¥29.47 | ¥1.74 | 97.9% | |
| fp8 | 1.05M | ¥9.38 | ¥29.47 | ¥0.94 | 100.0% | |
| fp8 | 1.00M | ¥9.38 | ¥29.47 | ¥1.74 | 99.7% | |
G GMICloud | fp8 | 1.05M | ¥9.38 | ¥29.47 | ¥1.74 | 100.0% |
| fp4 | 262K | ¥9.38 | ¥29.47 | ¥1.74 | 99.2% | |
| — | 1.05M | ¥9.38 | ¥29.47 | ¥1.74 | 99.9% | |
| fp8 | 1.05M | ¥9.38 | ¥29.47 | ¥1.74 | 99.7% | |
| — | 1.05M | ¥10.32 | ¥32.42 | ¥1.03 | 100.0% | |
| fp8 | 1.05M | ¥14.07 | ¥44.21 | ¥1.41 | 99.7% | |
| fp8 | 1.05M | ¥14.07 | ¥44.21 | ¥1.41 | 99.7% | |
| fp4 | 1.05M | ¥15.07 | ¥52.78 | ¥3.75 | 100.0% | |
| fp8 | 1.00M | ¥15.47 | ¥48.63 | ¥3.09 | 98.6% | |
D Decart | fp4 | 1.05M | ¥16.75 | ¥60.29 | ¥3.62 | 100.0% |
W
Waferfp4¥0.23
输入/M
¥46.89
输出/M
¥0.22
缓存/M
100.0%
可用率
¥0.53
输入/M
¥40.19
输出/M
¥0.53
缓存/M
99.8%
可用率
¥1.27
输入/M
¥3.98
输出/M
¥0.24
缓存/M
100.0%
可用率
¥1.27
输入/M
¥53.59
输出/M
¥1.27
缓存/M
100.0%
可用率
W
Waferfp4¥1.27
输入/M
¥66.98
输出/M
¥1.21
缓存/M
100.0%
可用率
¥2.68
输入/M
¥26.79
输出/M
¥0.54
缓存/M
99.9%
可用率
¥3.01
输入/M
¥9.65
输出/M
¥0.56
缓存/M
94.8%
可用率
¥3.72
输入/M
¥11.69
输出/M
¥0.69
缓存/M
99.9%
可用率
¥3.77
输入/M
¥12.06
输出/M
¥0.70
缓存/M
100.0%
可用率
C
CoreWeavefp4¥4.15
输入/M
¥16.21
输出/M
¥0.94
缓存/M
97.1%
可用率
¥4.35
输入/M
¥13.68
输出/M
¥0.81
缓存/M
100.0%
可用率
I
Inceptronfp4¥4.62
输入/M
¥6.96
输出/M
¥0.94
缓存/M
99.3%
可用率
¥4.69
输入/M
¥14.74
输出/M
¥0.70
缓存/M
100.0%
可用率
S
SiliconFlowfp8限时 -50%¥4.69
输入/M
¥14.74
输出/M
¥0.87
缓存/M
99.8%
可用率
¥6.28
输入/M
¥19.75
输出/M
¥1.17
缓存/M
100.0%
可用率
¥6.47
输入/M
¥20.34
输出/M
¥1.29
缓存/M
98.1%
可用率
¥7.50
输入/M
¥23.58
输出/M
¥1.50
缓存/M
100.0%
可用率
P
Phalafp8¥8.44
输入/M
¥20.10
输出/M
¥1.47
缓存/M
23.5%
可用率
¥9.38
输入/M
¥29.47
输出/M
-
缓存/M
95.6%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥0.94
缓存/M
99.9%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥0.94
缓存/M
100.0%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥1.74
缓存/M
97.9%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥0.94
缓存/M
100.0%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥1.74
缓存/M
99.7%
可用率
G
GMICloudfp8¥9.38
输入/M
¥29.47
输出/M
¥1.74
缓存/M
100.0%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥1.74
缓存/M
99.2%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥1.74
缓存/M
99.9%
可用率
¥9.38
输入/M
¥29.47
输出/M
¥1.74
缓存/M
99.7%
可用率
¥10.32
输入/M
¥32.42
输出/M
¥1.03
缓存/M
100.0%
可用率
¥14.07
输入/M
¥44.21
输出/M
¥1.41
缓存/M
99.7%
可用率
¥14.07
输入/M
¥44.21
输出/M
¥1.41
缓存/M
99.7%
可用率
¥15.07
输入/M
¥52.78
输出/M
¥3.75
缓存/M
100.0%
可用率
¥15.47
输入/M
¥48.63
输出/M
¥3.09
缓存/M
98.6%
可用率
D
Decartfp4¥16.75
输入/M
¥60.29
输出/M
¥3.62
缓存/M
100.0%
可用率
📊 Artificial Analysis 综合指数
33.7
智能指数
68.8
编程指数
38.4
Agent 指数