Qwen3.5 122B-A10B | Qwen Vision-Language MoE API

Name: Qwen3.5 122b A10b API
Brand: qwen
Price: 0.4 USD
Availability: InStock

Utilizzo API

Usa i seguenti esempi di codice per integrare la nostra 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/qwen3.5-122b-a10b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Introduzione al modello

Qwen qwen3.5-122b-a10b

The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixtur

The Qwen3.5 122B-A10B 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. In terms of overall performance, this model is second only to Qwen3.5-397B-A17B. Its text capabilities significantly outperform those of Qwen3-235B-2507, and its visual capabilities surpass those of Qwen3-VL-235B.

Why It Looks Great

Large Language Model architecture for efficient processing
262144 context window for long document handling
Competitive pricing at $0.3/$2.1 per million tokens

Key Features

Context Window: 262144 tokens
Max Output: 65536 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	65536 tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.3
Output	$2.1

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/qwen3.5-122b-a10b

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/qwen3.5-122b-a10b",
    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/qwen3.5-122b-a10b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: qwen/qwen3.5-122b-a10b
Provider: Qwen

Qwen3.5 122b A10b API

qwen/qwen3.5-122b-a10b

Domande frequenti su Qwen3.5 122b A10b

Quanto costa Qwen3.5 122b A10b via API?+

Prezzi su WaveSpeedAI: $0.40 per milione di token in input e $3.20 per milione di token in output. Prompt caching e batch processing sono fatturati separatamente e riducono il costo effettivo su carichi lunghi e ripetitivi.

Qual è la context window di Qwen3.5 122b A10b?+

Qwen3.5 122b A10b supporta fino a 262K token di contesto e fino a 66K token di output per richiesta.

Qwen3.5 122b A10b è compatibile con OpenAI?+

Sì. WaveSpeedAI espone Qwen3.5 122b A10b tramite un endpoint compatibile con OpenAI all'indirizzo https://llm.wavespeed.ai/v1. Punta l'SDK ufficiale di OpenAI a questa base URL con la tua API key WaveSpeedAI — senza altre modifiche al codice.

Come si inizia con Qwen3.5 122b A10b?+

Accedi a WaveSpeedAI, crea una API key in Access Keys, poi invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. I nuovi account ricevono crediti gratuiti per testare Qwen3.5 122b A10b.

Prezzi