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

Data de lançamento: 2025-09-24

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

Preços

Pagamento por uso

Sem custo inicial, pague apenas pelo que usar

Entrada$0.30 / M Tokens

Saída$1.50 / M Tokens

Cache Read$0.11 / M Tokens

Experimentar o modelo

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

Online

Olá! Sou um assistente de IA útil. Em que posso ajudar?

Pronto para usar este modelo em um coding agent local?Setup do agente

Uso da API

Use os exemplos de código abaixo para integrar com nossa 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;
}

Introdução do 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

Info

Provedoralibaba

Tipollm

Funcionalidades suportadas

Entrada

TextoImagem

Saída

Texto

Contexto262,144

Saída máx.-

Vision✓ Suportado

Function Calling✓ Suportado

Guia de acesso à API

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

API Endpointchat/completions

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

Perguntas frequentes sobre Qwen3 Vl 235b A22b Instruct

Quanto custa Qwen3 Vl 235b A22b Instruct via API?+

Preços no WaveSpeedAI: $0.30 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 Vl 235b A22b Instruct?+

Qwen3 Vl 235b A22b Instruct suporta até 262K tokens de contexto e até — tokens de saída por requisição.

Qwen3 Vl 235b A22b Instruct é compatível com OpenAI?+

O WaveSpeedAI disponibiliza Qwen3 Vl 235b A22b Instruct em https://llm.wavespeed.ai/v1 pela interface Chat Completions compatível com OpenAI. Na maioria dos clientes OpenAI SDK, basta alterar a base URL e a chave API; campos opcionais dependem do modelo.

Como começo a usar o Qwen3 Vl 235b A22b Instruct?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys e envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Consulte o catálogo atual para disponibilidade, recursos e preços.