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alibaba
qwen/qwen3.7-max

qwen/qwen3.7-max

發布時間: 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.

定價

按用量付費

無需預付費用,僅按實際使用量付費

輸入$2.50 / M Tokens
輸出$7.50 / M Tokens
Cache Read$0.25 / M Tokens
Cache Write$3.13 / M Tokens

試用模型

qwen/qwen3.7-max
線上
alibaba
嗨!我是樂於助人的 AI 助理。有什麼可以幫你的嗎?
準備在本機編碼 Agent 中使用這個模型嗎?Agent 設定

API 使用

使用以下程式碼範例整合我們的 API:

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;
}

模型介紹

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

資訊

提供商alibaba
類型llm

支援功能

輸入
文字
輸出
文字
上下文1,000,000
最大輸出65,536
視覺-
函式呼叫✓ 支援

API 存取指南

Base URLhttps://llm.wavespeed.ai/v1
API 端點chat/completions
Model IDqwen/qwen3.7-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.

輸入

$2.5 /M

輸出

$7.5 /M

上下文

1000K

最大輸出

66K

工具調用

支援

在 WaveSpeedAI 試用 Qwen3.7 Max

透過我們的統一 API 接入 Qwen3.7 Max — 相容 OpenAI、無冷啟動、透明計費。

關於 Qwen3.7 Max 的常見問題

Qwen3.7 Max API 多少錢?+

WaveSpeedAI 定價:輸入每百萬 token $2.50,輸出每百萬 token $7.50。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。

Qwen3.7 Max 的上下文視窗有多大?+

Qwen3.7 Max 每次請求最多支援 1000K 上下文 token,輸出最多 66K token。

Qwen3.7 Max 是否相容 OpenAI?+

WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容 Chat Completions 介面提供 Qwen3.7 Max。大多數 OpenAI SDK 用戶端只需更換 base URL 和 API Key;選用欄位取決於具體模型。

如何開始使用 Qwen3.7 Max?+

登入 WaveSpeedAI,在 Access Keys 中建立 API Key,然後使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。模型可用性、能力和價格請以目前模型目錄為準。

相關 LLM API

Qwen3.7 Max | Qwen LLM API Pricing & Performance | WaveSpeedAI