qwen/qwen3.7-max
출시일: 2026-05-21
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
모델 사용해 보기
API 사용법
다음 코드 예시를 사용해 API와 연동하세요:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'qwen/qwen3.7-max',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'qwen/qwen3.7-max',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}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
| Specification | Value |
|---|---|
| Provider | alibaba |
| Model Type | Chat Completions model |
| Architecture | text->text |
| 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 |
| Primary Use Cases | Coding, office automation, productivity workflows, long-horizon agents, tool use |
| Release | May 2026 |
Pricing
| Token Type | Cost |
|---|---|
| Input | $2.50 per million tokens |
| Output | $7.50 per million tokens |
| Cache Write | $3.125 per million tokens |
How to Use
- Write your prompt - describe the task, provide context, and specify the desired output format.
- 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
지원 기능
API 접근 가이드
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?+
WaveSpeedAI는 https://llm.wavespeed.ai/v1의 OpenAI 호환 Chat Completions 인터페이스를 통해 Qwen3.7 Max을 제공합니다. 대부분의 OpenAI SDK 클라이언트는 base URL과 API 키를 변경해 사용할 수 있으며, 선택 필드는 모델에 따라 다릅니다.
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. 제공 여부, 기능 및 가격은 최신 모델 카탈로그를 확인하세요.