Qwen: Qwen3.5-Flash

qwen/qwen3.5-flash-02-23

1000KContext Window

66KMax Output

Supported Protocols:reasoninginclude_reasoningmax_tokenstemperaturetop_pseedpresence_penaltyresponse_formattoolstool_choicestructured_outputs

Normal

The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the 3 series, these models deliver a leap forward in performance for both pure text and multimodal tasks, offering fast response times while balancing inference speed and overall performance.

Capabilities

👁 Vision🧠 Reasoning🔧 Function CallingText GenerationCode GenerationAnalysis & ReasoningReasoning

Technical Specs

Input Modality

Text、Image、Video

Output Modality

Text

Arch

—

Default Temperature

0.7

Default Top_P

Pricing

Pay per use, no monthly fees

Billing Type	Unit	Price
Text Input	—	$0.0650/M tokens
Text Output	—	$0.2600/M tokens
Cache Write 1h	—	$0.0813/M tokens
Cache Write	—	$0.0813/M tokens

Quick Start

from openai import OpenAI

client = OpenAI(
    base_url="https://api.uniontoken.ai/v1",
    api_key="YOUR_UNIONTOKEN_API_KEY",
)

response = client.chat.completions.create(
    model="qwen/qwen3.5-flash-02-23",
    messages=[
        {"role": "user", "content": "Hello!"}
    ],
)

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