qwen/qwen3.6-flash
Data di rilascio: 2026-04-27
1,000,000 context · $0.25/M input tokens · $1.50/M output tokens
Qwen3.6 Flash is a fast, efficient multimodal language model from Alibaba’s Qwen 3.6 series. It supports text, image, and video inputs with a 1M-token context window and up to 64K output tokens. The model is designed for high-throughput chat, lightweight agent workflows, long-document understanding, visual reasoning, summarization, extraction, and cost-sensitive production workloads. It supports thinking mode, function calling, built-in tools, structured outputs, and batch calling.
Pay-per-use
Nessun costo iniziale, paga solo per ciò che usi
Usa i seguenti esempi di codice per integrare la nostra 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/qwen3.6-flash',
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/qwen3.6-flash',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Qwen3.6 Flash is a fast, efficient multimodal language model from Alibaba’s Qwen 3.6 series. It supports text, image, and video inputs with a 1M-token context window, making it a strong fit for high-volume chat, lightweight agents, long-document workflows, visual understanding, summarization, and structured extraction.
| Specification | Value |
|---|---|
| Provider | alibaba |
| Model Type | Chat Completions model |
| Architecture | text+image+video->text |
| Context Window | 1,000,000 tokens |
| Max Input | 934,464 tokens |
| Max Output | 65,536 tokens |
| Thinking Budget | 128K tokens |
| Input | Text, Image, Video |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Built-in Tools | Supported |
| Structured Outputs | Supported |
| Batch Calling | Supported |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: qwen/qwen3.6-flash
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/qwen3.6-flash",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)qwen/qwen3.6-flash
Qwen3.6 Flash is a fast, efficient multimodal language model from Alibaba’s Qwen 3.6 series. It supports text, image, and video inputs with a 1M-token context window and up to 64K output tokens. The model is designed for high-throughput chat, lightweight agent workflows, long-document understanding, visual reasoning, summarization, extraction, and cost-sensitive production workloads. It supports thinking mode, function calling, built-in tools, structured outputs, and batch calling.
Input
$0.25 /M
Output
$1.5 /M
Contesto
1000K
Output max
66K
Vision
Supportato
Uso strumenti
Supportato
Accedi a Qwen3.6 Flash tramite la nostra API unificata — compatibile con OpenAI, senza cold start, prezzi trasparenti.
Prezzi su WaveSpeedAI: $0.25 per milione di token in input e $1.50 per milione di token in output. Prompt caching e batch processing sono fatturati separatamente e riducono il costo effettivo su carichi lunghi e ripetitivi.
Qwen3.6 Flash supporta fino a 1000K token di contesto e fino a 66K token di output per richiesta.
WaveSpeedAI espone Qwen3.6 Flash su https://llm.wavespeed.ai/v1 tramite l’interfaccia Chat Completions compatibile con OpenAI. Per la maggior parte dei client OpenAI SDK basta cambiare base URL e API key; i campi opzionali dipendono dal modello.
Accedi a WaveSpeedAI, crea una API key in Access Keys e invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. Consulta il catalogo attuale per disponibilità, funzionalità e prezzi.