Qwen3.5 Flash

在线体验

silvamux/qwen3.5-flash

支持模态

text·image·video

输入价格¥0.2-1.2per 1M tokens

输出价格¥2-12per 1M tokens

上下文1M

发布日期2026-02-25

价格

以单次请求的输入上下文长度判定档位，Tune 与 Pro 采用相同的阶梯价格。

单位：每 100 万 tokens

输入上下文	输入	输出	缓存读取	缓存写入
≤ 131.072K tokens	¥0.2	¥2	¥0.02	¥0.25
≤ 262.144K tokens	¥0.8	¥8	¥0.08	¥1
> 262.144K tokens	¥1.2	¥12	¥0.12	¥1.5

模型能力

评测数据暂未可用

服务表现

暂未提供服务表现数据

Qwen3.5 Flash 的示例代码和 API

Proqwen3.5-flash

/api/v0/chat/completions/api/v1/chat/completions/api/anthropic/v1/messages

统一入口OpenAIAnthropic

curl https://www.silvamux.com/api/v1/chat/completions \
  -H "Authorization: Bearer 你的API密钥" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3.5-flash",
    "messages": [{"role": "user", "content": "你好，请介绍一下自己"}]
  }'

# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://www.silvamux.com/api/v1",
    api_key="你的API密钥",
)

response = client.chat.completions.create(
    model="qwen3.5-flash",
    messages=[
        {"role": "user", "content": "你好，请介绍一下自己"}
    ],
)

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\":\"qwen3.5-flash\",\"messages\":[{\"role\":\"user\",\"content\":\"你好，请介绍一下自己\"}]}";

Request request = new Request.Builder()
    .url("https://www.silvamux.com/api/v1/chat/completions")
    .header("Authorization", "Bearer 你的API密钥")
    .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: '你的API密钥',
})

const response = await client.chat.completions.create({
  model: 'qwen3.5-flash',
  messages: [{ role: 'user', content: '你好，请介绍一下自己' }],
})

console.log(response.choices[0].message.content)