Explore Qwen3.5-Flash for Multimodal Tasks

Qwen3.5-Flash efficiently processes text, images, and video.

Input: text · image · video Output: text Context: 1,000,000 tokens Release: 2026-02-25

Introducing Qwen3.5-Flash from Qwen, released on February 25, 2026. This advanced model features a context length of 1,000,000 and supports text, image, and video inputs to generate text outputs. Built on a hybrid architecture that combines linear attention with a sparse mixture-of-experts model, Qwen3.5-Flash enhances performance for both text and multimodal tasks. Experience fast response times and improved inference efficiency, making it suitable for a variety of applications. Whether you're working with text, images, or video, this model is designed to deliver effective results.

Use Cases

Here are a few ways teams apply Qwen: Qwen3.5-Flash in practice—from fast drafting to multimodal understanding. Adapt these ideas to your workflow.

Transform videos into concise text summaries

Generate text descriptions from images

Analyze text content alongside visual data

Create interactive content using multimodal inputs

Key Features

A quick look at the capabilities that make this model useful in real projects.

Hybrid architecture for enhanced efficiency

Supports text, image, and video inputs

Generates text outputs from multimodal data

High context length of 1,000,000

Fast response times for various tasks

Specs

Overview

Vendor
qwen

Model ID
qwen/qwen3.5-flash-02-23

Release
2026-02-25

Modalities & context

Input
text · image · video

Output
text

Context
1,000,000 tokens

Parameters & defaults

Supported parameters: include_reasoning, max_tokens, presence_penalty, reasoning, response_format, seed, structured_outputs, temperature, tool_choice, tools, top_p

Defaults: temperature 0.2, top_p 0.95

Benchmark tests: Qwen: Qwen3.5-Flash

We ran this model against a few representative prompts to show its range. Review the outputs below and be the judge.

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