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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.

가격

사용량 기반 과금

선결제 없이 사용한 만큼만 지불

입력$0.60 / M Tokens
출력$3.60 / M Tokens

API 사용법

다음 코드 예시를 사용해 API와 연동하세요:

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)

모델 소개

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

정보

제공자qwen
유형llm

지원 기능

입력
텍스트이미지
출력
텍스트
컨텍스트262,144
최대 출력65,536
Vision✓ 지원
Function Calling✓ 지원

API 접근 가이드

Base URLhttps://llm.wavespeed.ai/v1
API 엔드포인트chat/completions
모델 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.

입력

$0.6 /M

출력

$3.6 /M

컨텍스트

262K

최대 출력

66K

Vision

지원

도구 사용

지원

WaveSpeedAI에서 Qwen3.5 397b A17b 체험

통합 API를 통해 Qwen3.5 397b A17b 액세스 — OpenAI 호환, 콜드 스타트 없음, 투명한 가격.

Playground 열기

Qwen3.5 397b A17b에 대해 자주 묻는 질문

Qwen3.5 397b A17b API 비용은 얼마인가요?+

WaveSpeedAI 가격: 입력 토큰 100만 개당 $0.60, 출력 토큰 100만 개당 $3.60. 프롬프트 캐싱과 배치 처리는 별도로 청구되며 긴 반복 작업에서 실질 비용을 줄여 줍니다.

Qwen3.5 397b A17b의 컨텍스트 윈도우는 얼마나 되나요?+

Qwen3.5 397b A17b은 요청당 최대 262K 컨텍스트 토큰과 최대 66K 출력 토큰을 지원합니다.

Qwen3.5 397b A17b은 OpenAI 호환인가요?+

네. WaveSpeedAI는 OpenAI 호환 엔드포인트 https://llm.wavespeed.ai/v1을 통해 Qwen3.5 397b A17b을 제공합니다. 공식 OpenAI SDK의 base URL을 이 주소로 변경하고 WaveSpeedAI API 키를 사용하면 코드 변경 없이 사용할 수 있습니다.

Qwen3.5 397b A17b을 어떻게 시작하나요?+

WaveSpeedAI에 로그인하고 Access Keys에서 API 키를 만든 다음, 위에 표시된 모델 ID로 https://llm.wavespeed.ai/v1/chat/completions에 요청을 보내세요. 신규 계정은 Qwen3.5 397b A17b을 평가할 수 있는 무료 크레딧을 받습니다.

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