Qwen3.6 27B | Qwen Multimodal LLM API Pricing

Name: Qwen3.6 27b API
Brand: qwen
Price: 0.54 USD
Availability: InStock

Uso da API

Use os exemplos de código abaixo para integrar com nossa 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/qwen3.6-27b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introdução do modelo

Qwen: Qwen3.6 27B

Qwen3.6 27B is a dense 27-billion-parameter multimodal language model from Alibaba’s Qwen Team. Released in April 2026, it supports text, image, and video inputs, combines strong language and visual reasoning, and is optimized for agentic coding, repository-level reasoning, document understanding, and tool-use workflows.

Why It Looks Great

Dense 27B architecture for practical deployment and predictable inference behavior
Native multimodal support for text, image, and video understanding
262K-token context window for long prompts, large codebases, documents, and multi-turn workflows
Up to 80K output tokens for extended reasoning, coding, and structured generation
Strong agentic coding performance at a deployable open-weight scale
Supports both thinking and non-thinking modes for flexible latency and reasoning trade-offs
Function calling and tool-use support for agentic application workflows
Structured output support for JSON responses and schema-constrained generation

Key Features

Parameters: 27B
Architecture: Dense
Context Window: 262,144 tokens
Max Input: 180,224 tokens
Max Output: 81,920 tokens
Input: Text, Image, Video
Output: Text
Vision: Supported
Function Calling: Supported
Structured Outputs: Supported
Thinking Mode: Supported
Audio Input: Not listed
Image Generation: Not listed
Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

Specifications

Specification	Value
Provider	alibaba
Model Type	Chat Completions model
Architecture	Dense 27B multimodal model
Modalities	text+image+video->text
Context Window	262,144 tokens
Max Input	180,224 tokens
Max Output	81,920 tokens
Input	Text, Image, Video
Output	Text
Vision	Supported
Function Calling	Supported
Structured Outputs	Supported
Release	April 2026

Pricing

Token Type	Cost
Input	$0.32 per million tokens
Output	$3.20 per million tokens

How to Use

Write your prompt - describe the task, provide context, and specify the 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/qwen3.6-27b

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/qwen3.6-27b",
    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/qwen3.6-27b",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: qwen/qwen3.6-27b
Provider: alibaba
Best suited for agentic coding, repository-level reasoning, multimodal reasoning, document understanding, and structured output workflows

Qwen3.6 27b API

qwen/qwen3.6-27b

Qwen3.6 27B is a dense 27-billion-parameter multimodal language model from Alibaba’s Qwen Team, released in April 2026. It supports text, image, and video inputs with a 262K-token context window and up to 80K output tokens. Designed for agentic coding, repository-level reasoning, multimodal reasoning, document understanding, and tool-use workflows, it supports both thinking and non-thinking modes while remaining practical to deploy at a widely used 27B dense-model scale.

Perguntas frequentes sobre Qwen3.6 27b

Quanto custa Qwen3.6 27b via API?+

Preços no WaveSpeedAI: $0.54 por milhão de tokens de entrada e $3.24 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.

Qual é a janela de contexto do Qwen3.6 27b?+

Qwen3.6 27b suporta até 262K tokens de contexto e até 82K tokens de saída por requisição.

Qwen3.6 27b é compatível com OpenAI?+

Sim. O WaveSpeedAI expõe o Qwen3.6 27b através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.

Como começo a usar o Qwen3.6 27b?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Qwen3.6 27b.

Preços

Experimentar o modelo