qwen/qwen3.7-max
リリース日: 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.
料金
従量課金
初期費用なし、使った分だけお支払い
モデルを試す
API 利用
以下のコード例を使用して API と連携してください:
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;
}モデル紹介
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
情報
対応機能
API アクセスガイド
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.
入力
$2.5 /M
出力
$7.5 /M
コンテキスト
1000K
最大出力
66K
ツール利用
対応
Qwen3.7 Maxに関するよくある質問
Qwen3.7 Max API の料金はいくらですか?+
WaveSpeedAI の料金: 入力 100 万トークンあたり $2.50、出力 100 万トークンあたり $7.50。プロンプトキャッシュとバッチ処理は別途料金で、長く反復的なワークロードでは実効コストを下げられます。
Qwen3.7 Max のコンテキストウィンドウはどのくらいですか?+
Qwen3.7 Max はリクエストあたり最大 1000K のコンテキストトークンと最大 66K の出力トークンをサポートします。
Qwen3.7 Max は OpenAI 互換ですか?+
WaveSpeedAI は https://llm.wavespeed.ai/v1 の OpenAI 互換 Chat Completions インターフェースで Qwen3.7 Max を提供します。多くの OpenAI SDK クライアントはベース URL と API キーの変更で利用できますが、オプション項目はモデルごとに異なります。
Qwen3.7 Max を使い始めるには?+
WaveSpeedAI にサインインし、Access Keys で API キーを作成して、上に表示されたモデル ID を指定して https://llm.wavespeed.ai/v1/chat/completions にリクエストを送信してください。提供状況、機能、料金は最新のモデルカタログで確認してください。