qwen/qwen3.5-27b
Release date: 2026-02-26
262,144 context · $0.20/M input tokens · $1.56/M output tokens
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of the Qwen3.5-122B-A10B.
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 os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["WAVESPEED_API_KEY"],
base_url="https://llm.wavespeed.ai/v1",
timeout=120.0,
max_retries=2,
)
try:
response = client.chat.completions.create(
model="qwen/qwen3.5-27b",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content or "")
except Exception as exc:
raise SystemExit(f"LLM request failed: {exc}") from excModel Introduction
Qwen qwen3.5-27b
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of the Qwen3.5-122B-A10B.
Why It Looks Great
- Large Language Model architecture for efficient processing
- 262144 context window for long document handling
- Competitive pricing at $0.2/$1.6 per million tokens
Key Features
- Context Window: 262144 tokens
- Max Output: 65536 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Qwen |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 262144 tokens |
| Max Output | 65536 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.2 |
| Output | $1.6 |
How to Use
- Write your prompt — describe the task, provide context, and specify 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/qwen3.5-27b
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/qwen3.5-27b",
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/qwen3.5-27b",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: qwen/qwen3.5-27b
- Provider: Qwen
Info
Supported Functionality
API Access Guide
Qwen3.5 27b API
qwen/qwen3.5-27b
The Qwen3.5 27B native vision-language Dense model incorporates a linear attention mechanism, delivering fast response times while balancing inference speed and performance. Its overall capabilities are comparable to those of the Qwen3.5-122B-A10B.
Input
$0.195 /M
Output
$1.56 /M
Context
262K
Max Output
66K
Vision
Supported
Tool Use
Supported
Try Qwen3.5 27b on WaveSpeedAI
Access Qwen3.5 27b through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Frequently Asked Questions about Qwen3.5 27b
How much does Qwen3.5 27b cost via the API?+
Pricing on WaveSpeedAI: $0.20 per million input tokens and $1.56 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 Qwen3.5 27b?+
Qwen3.5 27b supports up to 262K tokens of context with up to 66K tokens of output per request.
Is Qwen3.5 27b OpenAI-compatible?+
WaveSpeedAI exposes Qwen3.5 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 Qwen3.5 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.