text·image·video
Glm 5v Turbo
silvamux/
glm-5v-turboGLM 5v Turbo面向企业知识检索、资料问答与检索增强生成提供稳定的模型能力,优势集中在信息检索/RAG和数学与科学推理,并支持图像、视频信息输入。适合需要兼顾任务理解与结果质量的产品和研发团队。
Pricing
Tiers are determined by the input context length of each request; Tune and Pro share the same tiered prices.
| Input context | Input | Output | Cache read | Cache write |
|---|---|---|---|---|
| ≤ 32.768K tokens | ¥5 | ¥22 | ¥1.2 | ¥0 |
| > 32.768K tokens | ¥7 | ¥26 | ¥1.8 | ¥0 |
Capabilities
GLM-5V Turbo 综合得分 81,表现优秀,是一款推理与检索能力突出的模型。信息检索 / RAG(95%)、数学与科学推理(93%)与文本理解(91%)表现突出,在知识密集型问答与专业分析场景中优势明显。相对而言,智能体协同(45%)较弱,多步骤工具编排能力一般。高准确率的理解与检索任务最能体现它的价值。
81/ 100
专项进阶能力
8 items智能体协同45%
7 questions · 主/客观混合
代码生成90%
10 questions · 客观
代码理解与调试75%
12 questions · 主观
创意写作79%
17 questions · 主观
信息检索 / RAG95%
13 questions · 主/客观混合
数学与科学推理93%
14 questions · 客观
长文本处理87%
3 questions · 主观
多语言能力89%
10 questions · 主/客观混合
通用基础能力
3 items通识知识76%
15 questions · 主/客观混合
文本理解91%
5 questions · 主观
逻辑推理74%
20 questions · 主/客观混合
安全与合规能力
2 items幻觉控制83%
9 questions · 主观
指令遵循80%
14 questions · 主观
Performance
Glm 5v Turbo
glm-5v-turboLast 24 hours · 131,362 requests
- First token · TTFT · P50
- 1726ms P95 1849 ms
- Output speed · TPS · P50
- 78tok/s P95 98 tok/s
- Full response · E2E · P50
- 6.01s P95 7.06 s
- Request success rate
- 97.24% 127,736 completed requests
24-hour availability
24 hours ago12 hours agoNow
Glm 5v Turbo example code and API
Pro
glm-5v-turbo/api/v0/chat/completions/api/v1/chat/completions/api/anthropic/v1/messagescurl https://www.silvamux.com/api/v1/chat/completions \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5v-turbo",
"messages": [{"role": "user", "content": "Hello, please introduce yourself"}]
}'# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://www.silvamux.com/api/v1",
api_key="YOUR_API_KEY",
)
response = client.chat.completions.create(
model="glm-5v-turbo",
messages=[
{"role": "user", "content": "Hello, please introduce yourself"}
],
)
print(response.choices[0].message.content)// Gradle: implementation(__HL_SLOT_0__)
import okhttp3.*;
OkHttpClient client = new OkHttpClient();
MediaType json = MediaType.get("application/json");
String payload = "{\"model\":\"glm-5v-turbo\",\"messages\":[{\"role\":\"user\",\"content\":\"Hello, please introduce yourself\"}]}";
Request request = new Request.Builder()
.url("https://www.silvamux.com/api/v1/chat/completions")
.header("Authorization", "Bearer YOUR_API_KEY")
.post(RequestBody.create(payload, json))
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}// npm install openai
import OpenAI from 'openai'
const client = new OpenAI({
baseURL: 'https://www.silvamux.com/api/v1',
apiKey: 'YOUR_API_KEY',
})
const response = await client.chat.completions.create({
model: 'glm-5v-turbo',
messages: [{ role: 'user', content: 'Hello, please introduce yourself' }],
})
console.log(response.choices[0].message.content)