qwen/qwen3.5-397b-a17b
262,144 context · $0.60/M input tokens · $3.60/M output tokens
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
Pago por uso
Sin costos iniciales, paga solo por lo que uses
Usa los siguientes ejemplos de código para integrar con nuestra 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/qwen3.5-397b-a17b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
| Specification | Value |
|---|---|
| Provider | Qwen |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 262144 tokens |
| Max Output | 65536 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.4 |
| Output | $2.3 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3.5-397b-a17b
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/qwen3.5-397b-a17b",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "qwen/qwen3.5-397b-a17b",
"messages": [{"role": "user", "content": "Hello!"}]
}'
qwen/qwen3.5-397b-a17b
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
Entrada
$0.6 /M
Salida
$3.6 /M
Contexto
262K
Salida máx.
66K
Visión
Compatible
Uso de herramientas
Compatible
Accede a Qwen3.5 397b A17b mediante nuestra API unificada — compatible con OpenAI, sin arranques en frío, precios transparentes.
Abrir PlaygroundPrecios en WaveSpeedAI: $0.60 por millón de tokens de entrada y $3.60 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.
Qwen3.5 397b A17b admite hasta 262K tokens de contexto y hasta 66K tokens de salida por solicitud.
Sí. WaveSpeedAI expone Qwen3.5 397b A17b a través de un endpoint compatible con OpenAI en https://llm.wavespeed.ai/v1. Apunta el SDK oficial de OpenAI a esta base URL con tu clave API de WaveSpeedAI — sin más cambios de código.
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. Las cuentas nuevas reciben créditos gratuitos para evaluar Qwen3.5 397b A17b antes de pagar por token.