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qwen
qwen/qwen3.5-397b-a17b

qwen/qwen3.5-397b-a17b

262,144 context · $0.60/M input tokens · $3.60/M output tokens

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.

定價

按用量付費

無需預付費用,僅按實際使用量付費

輸入$0.60 / M Tokens
輸出$3.60 / M Tokens

API 使用

使用以下程式碼範例整合我們的 API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="qwen/qwen3.5-397b-a17b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

模型介紹

Qwen qwen3.5-397b-a17b

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.


Why It Looks Great

  • Large Language Model architecture for efficient processing
  • 262144 context window for long document handling
  • Competitive pricing at $0.4/$2.3 per million tokens

Key Features

  • Context Window: 262144 tokens
  • Max Output: 65536 tokens
  • Vision: Supported
  • Function Calling: Supported

Specifications

SpecificationValue
ProviderQwen
Model TypeLarge Language Model (LLM)
ArchitectureN/A
Context Window262144 tokens
Max Output65536 tokens
InputText
OutputText
VisionSupported
Function CallingSupported

Pricing

Token TypeCost per Million Tokens
Input$0.4
Output$2.3

How to Use

  1. Write your prompt — describe the task, provide context, and specify desired output format.
  2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3.5-397b-a17b


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="qwen/qwen3.5-397b-a17b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "qwen/qwen3.5-397b-a17b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: qwen/qwen3.5-397b-a17b
  • Provider: Qwen

資訊

提供商qwen
類型llm

支援功能

輸入
文字影像
輸出
文字
上下文262,144
最大輸出65,536
視覺✓ 支援
函式呼叫✓ 支援

API 存取指南

Base URLhttps://llm.wavespeed.ai/v1
API 端點chat/completions
Model IDqwen/qwen3.5-397b-a17b

Qwen3.5 397b A17b API

qwen/qwen3.5-397b-a17b

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.

輸入

$0.6 /M

輸出

$3.6 /M

上下文

262K

最大輸出

66K

Vision

支援

工具調用

支援

在 WaveSpeedAI 試用 Qwen3.5 397b A17b

透過我們的統一 API 接入 Qwen3.5 397b A17b — 相容 OpenAI、無冷啟動、透明計費。

開啟 Playground

關於 Qwen3.5 397b A17b 的常見問題

Qwen3.5 397b A17b API 多少錢?+

WaveSpeedAI 定價:輸入每百萬 token $0.60,輸出每百萬 token $3.60。Prompt 快取與批次處理分別計費,可顯著降低長上下文、高重複任務的實際成本。

Qwen3.5 397b A17b 的上下文視窗有多大?+

Qwen3.5 397b A17b 每次請求最多支援 262K 上下文 token,輸出最多 66K token。

Qwen3.5 397b A17b 是否相容 OpenAI?+

是的。WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容端點提供 Qwen3.5 397b A17b。將官方 OpenAI SDK 的 base URL 指向該位址,使用 WaveSpeedAI 的 API Key 即可,無需其他程式碼變更。

如何開始使用 Qwen3.5 397b A17b?+

登入 WaveSpeedAI,在 Access Keys 建立 API Key,使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。新帳號將獲得免費額度,用於試用 Qwen3.5 397b A17b。

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