Qwen3 VL 235b A22b Instruct | Qwen LLM API

Name: Qwen3 Vl 235b A22b Instruct API
Brand: qwen
Price: 0.3 USD
Availability: InStock

qwen/qwen3-vl-235b-a22b-instruct

Fecha de lanzamiento: 2025-09-24

262,144 context · $0.30/M input tokens · $1.50/M output tokens

Precios

Pago por uso

Sin costos iniciales, paga solo por lo que uses

Entrada$0.30 / M Tokens

Salida$1.50 / M Tokens

Cache Read$0.11 / M Tokens

Probar el modelo

qwen/qwen3-vl-235b-a22b-instruct

En línea

¡Hola! Soy un asistente de IA útil. ¿En qué puedo ayudarte?

¿Listo para usar este modelo en un coding agent local?Configurar agent

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-vl-235b-a22b-instruct',
    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-vl-235b-a22b-instruct',
    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-vl-235b-a22b-instruct

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table extraction, multilingual OCR). The series emphasizes robust perception (recognition of diverse real-world and synthetic categories), spatial understanding (2D/3D grounding), and long-form visual comprehension, with competitive results on public multimodal benchmarks for both perception and reasoning.

Beyond analysis, Qwen3-VL supports agentic interaction and tool use: it can follow complex instructions over multi-image, multi-turn dialogues; align text to video timelines for precise temporal queries; and operate GUI elements for automation tasks. The models also enable visual coding workflows—turning sketches or mockups into code and assisting with UI debugging—while maintaining strong text-only performance comparable to the flagship Qwen3 language

Why It Looks Great

Large Language Model architecture for efficient processing
262144 context window for long document handling
Competitive pricing at $0.2/$0.10 per million tokens

Key Features

Context Window: 262144 tokens
Max Output: N/A tokens
Vision: Supported
Function Calling: Supported

Specifications

Specification	Value
Provider	Qwen
Model Type	Large Language Model (LLM)
Architecture	N/A
Context Window	262144 tokens
Max Output	tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.2
Output	$0.10

How to Use

Write your prompt — describe the task, provide context, and specify 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-vl-235b-a22b-instruct

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-vl-235b-a22b-instruct",
    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-vl-235b-a22b-instruct",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: qwen/qwen3-vl-235b-a22b-instruct
Provider: Qwen

Información

Proveedoralibaba

Tipollm

Funcionalidades compatibles

Entrada

TextoImagen

Salida

Texto

Contexto262,144

Salida máxima-

Visión✓ Compatible

Function Calling✓ Compatible

Guía de acceso a la API

Base URLhttps://llm.wavespeed.ai/v1

API Endpointchat/completions

ID del modeloqwen/qwen3-vl-235b-a22b-instruct

Preguntas frecuentes sobre Qwen3 Vl 235b A22b Instruct

¿Cuánto cuesta Qwen3 Vl 235b A22b Instruct a través de la API?+

Precios en WaveSpeedAI: $0.30 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 Vl 235b A22b Instruct?+

Qwen3 Vl 235b A22b Instruct admite hasta 262K tokens de contexto y hasta — tokens de salida por solicitud.

¿Es Qwen3 Vl 235b A22b Instruct compatible con OpenAI?+

WaveSpeedAI ofrece Qwen3 Vl 235b A22b Instruct 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 Vl 235b A22b Instruct?+

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.