qwen/qwen3.6-27b
Release date: 2026-04-27
262,144 context · $0.30/M input tokens · $2.00/M output tokens
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.
Pricing
Pay-per-use
No upfront costs, pay only for what you use
Try the model
API Usage
Use the following code examples to integrate with our 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/qwen3.6-27b',
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/qwen3.6-27b',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}Model Introduction
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
Info
Supported Functionality
API Access Guide
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.
Input
$0.3 /M
Output
$2 /M
Context
262K
Max Output
82K
Vision
Supported
Tool Use
Supported
Try Qwen3.6 27b on WaveSpeedAI
Access Qwen3.6 27b through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about Qwen3.6 27b
How much does Qwen3.6 27b cost via the API?+
Pricing on WaveSpeedAI: $0.30 per million input tokens and $2.00 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of Qwen3.6 27b?+
Qwen3.6 27b supports up to 262K tokens of context with up to 82K tokens of output per request.
Is Qwen3.6 27b OpenAI-compatible?+
WaveSpeedAI exposes Qwen3.6 27b at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.
How do I get started with Qwen3.6 27b?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.