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alibaba
qwen/qwen3.6-flash

qwen/qwen3.6-flash

1,000,000 context · $0.25/M input tokens · $1.50/M output tokens

Qwen3.6 Flash is a fast, efficient multimodal language model from Alibaba’s Qwen 3.6 series. It supports text, image, and video inputs with a 1M-token context window and up to 64K output tokens. The model is designed for high-throughput chat, lightweight agent workflows, long-document understanding, visual reasoning, summarization, extraction, and cost-sensitive production workloads. It supports thinking mode, function calling, built-in tools, structured outputs, and batch calling.

Preços

Pagamento por uso

Sem custo inicial, pague apenas pelo que usar

Entrada
256K $0.25 / M Tokens
> 256K $1.00 / M Tokens
Saída
256K $1.50 / M Tokens
> 256K $4.00 / M Tokens
Cache Read
256K $0.03 / M Tokens
> 256K $0.10 / M Tokens
Cache Write$0.31 / M Tokens

Experimentar o modelo

qwen/qwen3.6-flash
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/qwen3.6-flash",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introdução do modelo

Qwen: Qwen3.6 Flash

Qwen3.6 Flash is a fast, efficient multimodal language model from Alibaba’s Qwen 3.6 series. It supports text, image, and video inputs with a 1M-token context window, making it a strong fit for high-volume chat, lightweight agents, long-document workflows, visual understanding, summarization, and structured extraction.


Why It Looks Great

  • Fast, cost-efficient Qwen 3.6 model for high-throughput production workloads
  • Multimodal text, image, and video input support for visual and document understanding
  • 1M-token context window for long prompts, large files, and multi-turn workflows
  • Up to 64K output tokens for extended answers and structured generation
  • Thinking mode support for reasoning-heavy requests
  • Function calling and built-in tool support for agentic workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Batch calling support for large-scale offline or asynchronous workloads

Key Features

  • Context Window: 1,000,000 tokens
  • Max Input: 934,464 tokens
  • Max Output: 65,536 tokens
  • Input: Text, Image, Video
  • Output: Text
  • Vision: Supported
  • Function Calling: Supported
  • Built-in Tools: Supported
  • Structured Outputs: Supported
  • Batch Calling: Supported
  • Thinking Budget: up to 128K tokens
  • Supported Parameters: include_reasoning, max_tokens, presence_penalty, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_p

Specifications

SpecificationValue
Provideralibaba
Model TypeChat Completions model
Architecturetext+image+video->text
Context Window1,000,000 tokens
Max Input934,464 tokens
Max Output65,536 tokens
Thinking Budget128K tokens
InputText, Image, Video
OutputText
VisionSupported
Function CallingSupported
Built-in ToolsSupported
Structured OutputsSupported
Batch CallingSupported

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/qwen3.6-flash


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/qwen3.6-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)

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

Info

Provedoralibaba
Tipollm

Funcionalidades suportadas

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

Guia de acesso à API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID do modeloqwen/qwen3.6-flash

Qwen3.6 Flash API

qwen/qwen3.6-flash

Qwen3.6 Flash is a fast, efficient multimodal language model from Alibaba’s Qwen 3.6 series. It supports text, image, and video inputs with a 1M-token context window and up to 64K output tokens. The model is designed for high-throughput chat, lightweight agent workflows, long-document understanding, visual reasoning, summarization, extraction, and cost-sensitive production workloads. It supports thinking mode, function calling, built-in tools, structured outputs, and batch calling.

Entrada

$0.25 /M

Saída

$1.5 /M

Contexto

1000K

Saída máx.

66K

Vision

Suportado

Uso de ferramentas

Suportado

Experimente Qwen3.6 Flash no WaveSpeedAI

Acesse Qwen3.6 Flash através da nossa API unificada — compatível com OpenAI, sem inicializações a frio, preços transparentes.

Perguntas frequentes sobre Qwen3.6 Flash

Quanto custa Qwen3.6 Flash via API?+

Preços no WaveSpeedAI: $0.25 por milhão de tokens de entrada e $1.50 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 Qwen3.6 Flash?+

Qwen3.6 Flash suporta até 1000K tokens de contexto e até 66K tokens de saída por requisição.

Qwen3.6 Flash é compatível com OpenAI?+

Sim. O WaveSpeedAI expõe o Qwen3.6 Flash 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 Qwen3.6 Flash?+

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 Qwen3.6 Flash.

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