Vidu Q3·Q3 Pro 모델 50% 할인 · WaveSpeedAI 전용 | 5월 20일 – 6월 2일
alibaba
qwen/qwen3.7-max

qwen/qwen3.7-max

1,000,000 context · $2.50/M input tokens · $7.50/M output tokens

Qwen3.7-Max is Alibaba’s flagship model in the Qwen3.7 series, built for agent-centric text workflows. It is optimized for coding, debugging, office automation, productivity tasks, tool use, and long-horizon autonomous execution. With a 1M-token context window and up to 64K output tokens, it is well suited for large documents, repository-scale coding, multi-step planning, structured generation, and workflows that require sustained reasoning across hundreds or thousands of steps.

가격

사용량 기반 과금

선결제 없이 사용한 만큼만 지불

입력$2.50 / M Tokens
출력$7.50 / M Tokens
Cache Read$0.25 / M Tokens
Cache Write$3.13 / M Tokens

모델 사용해 보기

qwen/qwen3.7-max
온라인
alibaba
안녕하세요! 도움이 되는 AI 어시스턴트입니다. 무엇을 도와드릴까요?

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/qwen3.7-max",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

모델 소개

Qwen: Qwen3.7 Max

Qwen3.7-Max is Alibaba’s flagship model in the Qwen3.7 series, designed for agent-centric text workflows. It is optimized for coding, debugging, office automation, productivity tasks, tool use, and long-horizon autonomous execution.


Why It Looks Great

  • Flagship Qwen3.7 model built for agentic workloads
  • Strong fit for coding, debugging, office automation, productivity tasks, and tool use
  • 1M-token context window for long prompts, large documents, codebases, and multi-turn workflows
  • Up to 64K output tokens for extended reasoning, coding, and structured generation
  • Designed for long-horizon autonomous execution across complex multi-step tasks
  • Function calling and tool-use support for agentic application workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Reasoning controls for tuning latency, quality, and cost per request

Key Features

  • Context Window: 1,000,000 tokens
  • Max Input: 934,464 tokens
  • Max Output: 65,536 tokens
  • Input: Text
  • Output: Text
  • Vision: Not listed
  • Function Calling: Supported
  • Structured Outputs: Supported
  • Thinking Mode: Supported
  • Image Generation: Not listed
  • Audio Input: Not listed
  • Supported Parameters: include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_logprobs, top_p

Specifications

SpecificationValue
Provideralibaba
Model TypeChat Completions model
Architecturetext->text
Context Window1,000,000 tokens
Max Input934,464 tokens
Max Output65,536 tokens
InputText
OutputText
VisionNot listed
Function CallingSupported
Structured OutputsSupported
Thinking ModeSupported
Primary Use CasesCoding, office automation, productivity workflows, long-horizon agents, tool use
ReleaseMay 2026

Pricing

Token TypeCost
Input$2.50 per million tokens
Output$7.50 per million tokens
Cache Write$3.125 per million tokens

How to Use

  1. Write your prompt - describe the task, provide context, and specify the 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/qwen3.7-max


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/qwen3.7-max",
    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/qwen3.7-max",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: qwen/qwen3.7-max
  • Provider: alibaba
  • Best suited for coding agents, office automation, long-context text workflows, multi-step productivity tasks, tool use, and structured output generation

정보

제공자alibaba
유형llm

지원 기능

입력
텍스트
출력
텍스트
컨텍스트1,000,000
최대 출력65,536
Vision-
Function Calling✓ 지원

API 접근 가이드

Base URLhttps://llm.wavespeed.ai/v1
API 엔드포인트chat/completions
모델 IDqwen/qwen3.7-max

Qwen3.7 Max API

qwen/qwen3.7-max

Qwen3.7-Max is Alibaba’s flagship model in the Qwen3.7 series, built for agent-centric text workflows. It is optimized for coding, debugging, office automation, productivity tasks, tool use, and long-horizon autonomous execution. With a 1M-token context window and up to 64K output tokens, it is well suited for large documents, repository-scale coding, multi-step planning, structured generation, and workflows that require sustained reasoning across hundreds or thousands of steps.

입력

$2.5 /M

출력

$7.5 /M

컨텍스트

1000K

최대 출력

66K

도구 사용

지원

WaveSpeedAI에서 Qwen3.7 Max 체험

통합 API를 통해 Qwen3.7 Max 액세스 — OpenAI 호환, 콜드 스타트 없음, 투명한 가격.

Qwen3.7 Max에 대해 자주 묻는 질문

Qwen3.7 Max API 비용은 얼마인가요?+

WaveSpeedAI 가격: 입력 토큰 100만 개당 $2.50, 출력 토큰 100만 개당 $7.50. 프롬프트 캐싱과 배치 처리는 별도로 청구되며 긴 반복 작업에서 실질 비용을 줄여 줍니다.

Qwen3.7 Max의 컨텍스트 윈도우는 얼마나 되나요?+

Qwen3.7 Max은 요청당 최대 1000K 컨텍스트 토큰과 최대 66K 출력 토큰을 지원합니다.

Qwen3.7 Max은 OpenAI 호환인가요?+

네. WaveSpeedAI는 OpenAI 호환 엔드포인트 https://llm.wavespeed.ai/v1을 통해 Qwen3.7 Max을 제공합니다. 공식 OpenAI SDK의 base URL을 이 주소로 변경하고 WaveSpeedAI API 키를 사용하면 코드 변경 없이 사용할 수 있습니다.

Qwen3.7 Max을 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 Qwen3.7 Max을 평가할 수 있는 무료 크레딧을 받습니다.

관련 LLM API