qwen/qwen3-vl-8b-instruct
Fecha de lanzamiento: 2025-10-15
131,072 context · $0.08/M input tokens · $0.50/M output tokens
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
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-vl-8b-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-8b-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-8b-instruct
**Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, **
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon temporal reasoning, DeepStack for fine-grained visual-text alignment, and text-timestamp alignment for precise event localization.
The model supports a native 256K-token context window, extensible to 1M tokens, and handles both static and dynamic media inputs for tasks like document parsing, visual question answering, spatial reasoning, and GUI control. It achieves text understanding comparable to leading LLMs while expanding OCR coverage to 32 languages and enhancing robustness under varied visual conditions.
Why It Looks Great
- Large Language Model architecture for efficient processing
- 131072 context window for long document handling
- Competitive pricing at $0.1/$0.5 per million tokens
Key Features
- Context Window: 131072 tokens
- Max Output: 32768 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Qwen |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 131072 tokens |
| Max Output | 32768 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.1 |
| Output | $0.5 |
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-8b-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-8b-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-8b-instruct",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: qwen/qwen3-vl-8b-instruct
- Provider: Qwen
Información
Funcionalidades compatibles
Guía de acceso a la API
Qwen3 Vl 8b Instruct API
qwen/qwen3-vl-8b-instruct
Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
Entrada
$0.08 /M
Salida
$0.5 /M
Contexto
131K
Salida máx.
33K
Visión
Compatible
Uso de herramientas
Compatible
Prueba Qwen3 Vl 8b Instruct en WaveSpeedAI
Accede a Qwen3 Vl 8b Instruct mediante nuestra API unificada — compatible con OpenAI, sin arranques en frío, precios transparentes.
Preguntas frecuentes sobre Qwen3 Vl 8b Instruct
¿Cuánto cuesta Qwen3 Vl 8b Instruct a través de la API?+
Precios en WaveSpeedAI: $0.08 por millón de tokens de entrada y $0.50 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 8b Instruct?+
Qwen3 Vl 8b Instruct admite hasta 131K tokens de contexto y hasta 33K tokens de salida por solicitud.
¿Es Qwen3 Vl 8b Instruct compatible con OpenAI?+
WaveSpeedAI ofrece Qwen3 Vl 8b 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 8b 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.