qwen/qwen3.6-flash
Fecha de lanzamiento: 2026-04-27
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.
Precios
Pago por uso
Sin costos iniciales, paga solo por lo que uses
Probar el modelo
Uso de API
Usa los siguientes ejemplos de código para integrar con nuestra 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/qwen3.6-flash',
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/qwen3.6-flash',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Introducción del 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
| Specification | Value |
|---|---|
| Provider | alibaba |
| Model Type | Chat Completions model |
| Architecture | text+image+video->text |
| Context Window | 1,000,000 tokens |
| Max Input | 934,464 tokens |
| Max Output | 65,536 tokens |
| Thinking Budget | 128K tokens |
| Input | Text, Image, Video |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Built-in Tools | Supported |
| Structured Outputs | Supported |
| Batch Calling | Supported |
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/qwen3.6-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)Información
Funcionalidades compatibles
Guía de acceso a la API
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
Salida
$1.5 /M
Contexto
1000K
Salida máx.
66K
Visión
Compatible
Uso de herramientas
Compatible
Prueba Qwen3.6 Flash en WaveSpeedAI
Accede a Qwen3.6 Flash mediante nuestra API unificada — compatible con OpenAI, sin arranques en frío, precios transparentes.
Preguntas frecuentes sobre Qwen3.6 Flash
¿Cuánto cuesta Qwen3.6 Flash a través de la API?+
Precios en WaveSpeedAI: $0.25 por millón de tokens de entrada y $1.50 por millón de tokens de salida. El prompt caching y el procesamiento por lotes se facturan por separado y reducen el coste efectivo en cargas largas y repetitivas.
¿Cuál es la ventana de contexto de Qwen3.6 Flash?+
Qwen3.6 Flash admite hasta 1000K tokens de contexto y hasta 66K tokens de salida por solicitud.
¿Es Qwen3.6 Flash compatible con OpenAI?+
WaveSpeedAI ofrece Qwen3.6 Flash en https://llm.wavespeed.ai/v1 mediante la interfaz Chat Completions compatible con OpenAI. En la mayoría de clientes del SDK de OpenAI basta con cambiar la URL base y la clave API; los campos opcionales dependen del modelo.
¿Cómo empiezo con Qwen3.6 Flash?+
Inicia sesión en WaveSpeedAI, crea una clave API en Access Keys y envía una solicitud a https://llm.wavespeed.ai/v1/chat/completions con el id de modelo mostrado arriba. Consulta el catálogo actual para conocer disponibilidad, capacidades y precios.