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alibaba
qwen/qwen3.6-flash

qwen/qwen3.6-flash

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.

Prezzi

Pay-per-use

Nessun costo iniziale, paga solo per ciò che usi

Input
256K $0.25 / M Tokens
> 256K $1.00 / M Tokens
Output
256K $1.50 / M Tokens
> 256K $4.00 / M Tokens
Cache Read
256K $0.03 / M Tokens
> 256K $0.10 / M Tokens
Cache Write$0.31 / M Tokens

Prova il modello

qwen/qwen3.6-flash
Online
alibaba
Ciao! Sono un assistente IA utile. Come posso aiutarti?

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/qwen3.6-flash",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introduzione al modello

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, making it a strong fit for high-volume chat, lightweight agents, long-document workflows, visual understanding, summarization, and structured extraction.


Why It Looks Great

  • Fast, cost-efficient Qwen 3.6 model for high-throughput production workloads
  • Multimodal text, image, and video input support for visual and document understanding
  • 1M-token context window for long prompts, large files, and multi-turn workflows
  • Up to 64K output tokens for extended answers and structured generation
  • Thinking mode support for reasoning-heavy requests
  • Function calling and built-in tool support for agentic workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Batch calling support for large-scale offline or asynchronous workloads

Key Features

  • Context Window: 1,000,000 tokens
  • Max Input: 934,464 tokens
  • Max Output: 65,536 tokens
  • Input: Text, Image, Video
  • Output: Text
  • Vision: Supported
  • Function Calling: Supported
  • Built-in Tools: Supported
  • Structured Outputs: Supported
  • Batch Calling: Supported
  • Thinking Budget: up to 128K tokens
  • Supported Parameters: include_reasoning, max_tokens, presence_penalty, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_p

Specifications

SpecificationValue
Provideralibaba
Model TypeChat Completions model
Architecturetext+image+video->text
Context Window1,000,000 tokens
Max Input934,464 tokens
Max Output65,536 tokens
Thinking Budget128K tokens
InputText, Image, Video
OutputText
VisionSupported
Function CallingSupported
Built-in ToolsSupported
Structured OutputsSupported
Batch CallingSupported

How to Use

  1. Write your prompt - describe the task, provide context, and specify the desired output format.
  2. 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/qwen3.6-flash


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/qwen3.6-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)

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

Info

Provideralibaba
Tipollm

Funzionalità supportate

Input
TestoImmagine
Output
Testo
Contesto1,000,000
Output massimo65,536
Vision✓ Supportato
Function Calling✓ Supportato

Guida all'accesso API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID modelloqwen/qwen3.6-flash

Qwen3.6 Flash API

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

Prova Qwen3.6 Flash su WaveSpeedAI

Accedi a Qwen3.6 Flash tramite la nostra API unificata — compatibile con OpenAI, senza cold start, prezzi trasparenti.

Domande frequenti su Qwen3.6 Flash

Quanto costa Qwen3.6 Flash via API?+

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.

Qual è la context window di Qwen3.6 Flash?+

Qwen3.6 Flash supporta fino a 1000K token di contesto e fino a 66K token di output per richiesta.

Qwen3.6 Flash è compatibile con OpenAI?+

Sì. WaveSpeedAI espone Qwen3.6 Flash 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 Qwen3.6 Flash?+

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 Qwen3.6 Flash.

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