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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.

Preços

Pagamento por uso

Sem custo inicial, pague apenas pelo que usar

Entrada$2.50 / M Tokens
Saída$7.50 / M Tokens
Cache Read$0.25 / M Tokens
Cache Write$3.13 / M Tokens

Experimentar o modelo

qwen/qwen3.7-max
Online
alibaba
Olá! Sou um assistente de IA útil. Em que posso ajudar?

Uso da API

Use os exemplos de código abaixo para integrar com nossa API:

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)

Introdução do modelo

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

Info

Provedoralibaba
Tipollm

Funcionalidades suportadas

Entrada
Texto
Saída
Texto
Contexto1,000,000
Saída máx.65,536
Vision-
Function Calling✓ Suportado

Guia de acesso à API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID do modeloqwen/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.

Entrada

$2.5 /M

Saída

$7.5 /M

Contexto

1000K

Saída máx.

66K

Uso de ferramentas

Suportado

Experimente Qwen3.7 Max no WaveSpeedAI

Acesse Qwen3.7 Max através da nossa API unificada — compatível com OpenAI, sem inicializações a frio, preços transparentes.

Perguntas frequentes sobre Qwen3.7 Max

Quanto custa Qwen3.7 Max via API?+

Preços no WaveSpeedAI: $2.50 por milhão de tokens de entrada e $7.50 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.

Qual é a janela de contexto do Qwen3.7 Max?+

Qwen3.7 Max suporta até 1000K tokens de contexto e até 66K tokens de saída por requisição.

Qwen3.7 Max é compatível com OpenAI?+

Sim. O WaveSpeedAI expõe o Qwen3.7 Max através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.

Como começo a usar o Qwen3.7 Max?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Qwen3.7 Max.

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