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qwen3.5-plus
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Qwen3.5 Plus

qwen3.5-plus
Qwen
The Qwen 3.5 native vision-language Plus model is built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In multiple task evaluations, the 3.5 series has demonstrated outstanding performance comparable to current leading frontier models, with leapfrog improvements over the 3 series in both pure-text and multimodal capabilities. This model version is functionally equivalent to the snapshot model qwen3.5-plus-2026-02-15.

Pricing

TierPricingWeb SearchCache WriteCache Read
Input<=128K
$0.110$0.658
$0.000548/request$0.137/M tokens$0.01096/M tokens
128K<Input<=256K
$0.274$1.644
$0.000548/request$0.3425/M tokens$0.0274/M tokens
256K<Input<=1000K
$0.548$3.288
$0.000548/request$0.685/M tokens$0.0548/M tokens

Input Modalities

  • Text
  • Vision
  • Video

Output Modalities

  • Text

Capabilities

  • Thinking
  • Web
  • Tools
  • Tool calling
  • Structured outputs
  • Long context

Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://aihubmix.com/v1",
)

response = client.chat.completions.create(
    model="qwen3.5-plus",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

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

Frequently asked questions

What is qwen3.5-plus?

The Qwen 3.5 native vision-language Plus model is built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In multiple task evaluations, the 3.5 series has demonstrated outstanding performance comparable to current leading frontier models, with leapfrog improvements over the 3 series in both pure-text and multimodal capabilities. This model version is functionally equivalent to the snapshot model qwen3.5-plus-2026-02-15.
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