Qwen3.6 27B | Qwen Multimodal LLM API Pricing

Name: Qwen3.6 27b API
Brand: qwen
Price: 0.54 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/qwen3.6-27b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introduzione al modello

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.

Domande frequenti su Qwen3.6 27b

Quanto costa Qwen3.6 27b via API?+

Prezzi su WaveSpeedAI: $0.54 per milione di token in input e $3.24 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 27b?+

Qwen3.6 27b supporta fino a 262K token di contesto e fino a 82K token di output per richiesta.

Qwen3.6 27b è compatibile con OpenAI?+

Sì. WaveSpeedAI espone Qwen3.6 27b 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 27b?+

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 27b.

Prezzi

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