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Glm 4.7 Flash
silvamux/
glm-4.7-FlashGLM 4.7 Flash是一款侧重代码生成的模型,在文本理解方面也有较好表现。它适合处理代码编写、重构与开发辅助,可作为相关业务流程中的理解、推理或生成能力底座。
Pricing
Tune and Pro share the same prices.
| Input context | Input | Output | Cache read | Cache write |
|---|---|---|---|---|
| - | ¥0 / 1M tokens | ¥0 / 1M tokens | ¥0 / 1M tokens | ¥0 / 1M tokens |
Capabilities
GLM-4.7 Flash 综合得分 63,整体能力中等,是一款特点鲜明的轻量代码模型。代码生成(99%)表现突出,文本理解(86%)与多语言能力(84%)也保持可用水准,在轻量代码研发与内容分析场景中有较高性价比。相对而言,长文本处理(17%)明显不足,长文档任务存在明显盲区。代码生成类高频轻量任务最能发挥它的价值。
63/ 100
专项进阶能力
8 items智能体协同22%
7 questions · 主/客观混合
代码生成99%
10 questions · 客观
代码理解与调试48%
12 questions · 主/客观混合
创意写作73%
17 questions · 主观
信息检索 / RAG75%
13 questions · 主/客观混合
长文本处理17%
3 questions · 主/客观混合
数学与科学推理71%
14 questions · 客观
多语言能力84%
10 questions · 主/客观混合
通用基础能力
3 items通识知识73%
15 questions · 主/客观混合
文本理解86%
5 questions · 主观
逻辑推理64%
20 questions · 主/客观混合
安全与合规能力
2 items幻觉控制53%
9 questions · 主/客观混合
指令遵循54%
14 questions · 主/客观混合
Performance
Glm 4.7 Flash
glm-4.7-FlashLast 24 hours · 103,972 requests
- First token · TTFT · P50
- 805ms P95 2217 ms
- Output speed · TPS · P50
- 81tok/s P95 86 tok/s
- Full response · E2E · P50
- 9.52s P95 9.61 s
- Request success rate
- 99.27% 103,214 completed requests
24-hour availability
24 hours ago12 hours agoNow
Glm 4.7 Flash example code and API
Pro
glm-4.7-Flash/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-4.7-Flash",
"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-4.7-Flash",
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-4.7-Flash\",\"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-4.7-Flash',
messages: [{ role: 'user', content: 'Hello, please introduce yourself' }],
})
console.log(response.choices[0].message.content)