Qwen 3.5: Native Multimodal Architecture and How It Fits Into AI Video Workflows

Qwen 3.5: Native Multimodal Architecture and How It Fits Into AI Video Workflows

Alibaba has officially unveiled the Qwen 3.5 model family, marking a new stage in its large model roadmap. The launch includes open‑weight models and commercial variants like Qwen 3.5‑Plus, and is built around a “native multimodal” design that can handle text, images, and video.

In this article, we’ll focus on what has been publicly shared about the Qwen 3.5 series so far, and then explore how models like Qwen 3.5 can work together with cinematic AI video generators such as Seedance 2.0 on Seedance2.today (Seedance 2.0: https://www.seedance2.today/, AI Video Generator: https://www.seedance2.today/ai-video-generator).

What Is Qwen 3.5? 

Qwen 3.5 is Alibaba’s new generation of large models in the Qwen family, introduced around Lunar New Year 2026. According to Alibaba’s own documentation and third‑party coverage:

• Qwen 3.5 is positioned as a next‑generation model series with architectural changes compared to earlier Qwen 3 releases.

• The family includes open‑source / open‑weight models, with different sizes (for example dense 2B and larger MoE variants) aimed at community and enterprise deployment.

• The series is designed as native multimodal, meaning the architecture is built to handle text and vision together rather than adding vision as a superficial extension.

• Qwen 3.5 is described as delivering performance competitive with top international models across language understanding, reasoning, coding, and other benchmarks, based on Alibaba’s reported evaluations.

On top of the open‑weight models, Alibaba also provides closed‑source commercial versions such as Qwen 3.5‑Plus via Alibaba Cloud’s Model Studio, which add long‑context and production‑grade hosting.

Architecture: Hybrid Design and MoE 

Technical write‑ups about Qwen 3.5 point to several recurring ideas in the architecture:

Hybrid backbone

The Qwen 3.5 series adopts a hybrid design that blends components such as Gated DeltaNet‑style layers and hybrid attention mechanisms. This is intended to improve efficiency on long sequences while preserving modeling power on shorter contexts.

Mixture‑of‑Experts (MoE)

Higher‑end Qwen 3.5 variants use sparse MoE, where only a subset of “experts” are active for each token. This allows:

• Higher effective parameter counts,

• Lower per‑token compute on average,

• Better scaling of reasoning capacity without linear cost growth.

Native multimodal design

Qwen 3.5 is described as a native multimodal series rather than a purely text‑only family. Vision capabilities are attached at the architectural level, enabling the model to:

• Accept text and images together as input,

• Work with video frames as part of its vision pipeline in some variants,

• Use a shared representation space across modalities.

This makes Qwen 3.5 suitable not only for chat and code, but also for understanding and describing visual content, which is directly relevant to AI video workflows.

Model Lineup: Open‑Source and Commercial Variants 

Based on public information, the Qwen 3.5 family includes:

• Open‑weight dense models in smaller sizes (for example around 2B parameters), suitable for on‑prem or custom deployments.

• Larger MoE models with significantly more total parameters, but with only a subset of parameters active per token, improving efficiency.

• Qwen 3.5‑Plus, a commercial multimodal model hosted on Alibaba Cloud with a context window advertised at up to 1 million tokens, and pricing published on the Model Studio page.

• Related flagships such as Qwen 3‑Max‑Thinking, which focus on advanced reasoning and are often used as comparison points in benchmarks.

These models are being integrated across ecosystems: Hugging Face Transformers has merged support for Qwen 3.5, and several inference frameworks have added back‑end compatibility.

How Qwen 3.5 and Seedance 2.0 Complement Each Other 

Qwen 3.5 is a large language and multimodal model. Seedance 2.0, available via Seedance2.today (Seedance 2.0: https://www.seedance2.today/, AI Video Generator: https://www.seedance2.today/ai-video-generator), is a dedicated AI video generation model that focuses on turning text and images into cinematic videos with multi‑shot continuity and native audio.

They address different layers of the stack, but in practice they fit together:

1. Prompt and storyboard generation 

High‑quality video output from Seedance 2.0 benefits from precise prompts and scene descriptions. Qwen 3.5 can help:

• Turn a short idea into a full script or narrative outline.

• Break down a story into shot‑by‑shot descriptions that can be copied into Seedance 2.0’s Text‑to‑Video workflow.

• Generate multiple prompt variations to test on Seedance2.today, helping you explore different visual directions without manually rewriting everything.

2. Multimodal analysis of reference images and video 

Because Qwen 3.5 is designed as a multimodal model, it can analyze images and frames and then produce useful text for Seedance prompts:

• Describe the style, lighting, camera angle, and subject composition of a still frame.

• Suggest ways to extend that frame into a multi‑shot sequence that Seedance 2.0 can generate.

• Help you build prompt templates that keep visual identity consistent across several Seedance generations.

Seedance 2.0 then uses those prompts on Seedance2.today to generate cinematic output with multi‑shot continuity, 2K‑class visual quality, and native audio.

3. Long‑context planning for campaigns 

Some Qwen 3.5 variants, especially commercial models like Qwen 3.5‑Plus, are advertised with very large context windows (up to 1M tokens). That makes them suitable for:

• Keeping entire campaign plans, product catalogs, and past scripts in context at once.

• Designing coherent content series where multiple Seedance videos share characters, tone, and visual language.

• Managing prompt libraries that you reuse across many Seedance 2.0 generations.

From there, you can use Seedance2.today’s credit‑based system (Pricing: https://www.seedance2.today/pricing) to generate the actual videos at the resolutions and aspect ratios you need.

Seedance2.today’s Position in the Stack 

To avoid confusion, it’s helpful to restate the roles:

• Qwen 3.5 is a family of large models from Alibaba focused on language and multimodal reasoning, delivered as open weights and cloud‑hosted APIs.

• Seedance 2.0, accessed through Seedance2.today, is an AI video model that offers multi‑shot storytelling, up to 2K‑class output, persistent character identity, and native audio generation.

Seedance2.today itself does not host Qwen 3.5; instead, it serves as an independent, third‑party frontend for Seedance video models (Seedance 1.5 Pro and Seedance 2.0). The site is not affiliated with or endorsed by ByteDance or the official Seedance team, and is built on top of the Seedance API.

That means you are free to pair Seedance2.today with any LLM stack you prefer — including Qwen 3.5, Qwen 3.5‑Plus, or other open‑source and commercial models — to handle planning, scripting, and prompt engineering.

Putting It All Together in 2026 

The release of Qwen 3.5 shows how quickly large language and multimodal models are evolving on the text and reasoning side. At the same time, video models like Seedance 2.0 are pushing the boundaries of visual quality, motion, and audio synchronization.

For creators, marketers, and developers in 2026, a practical pattern is emerging:

• Use LLMs such as Qwen 3.5 to understand assets, plan campaigns, and generate detailed prompts and storyboards.

• Use Seedance 2.0 on Seedance2.today to turn those plans into cinematic multi‑shot videos with native audio, across the aspect ratios and resolutions you need.

If you are already working with Seedance 2.0 via the AI Video Generator (https://www.seedance2.today/ai-video-generator), the Qwen 3.5 family gives you another strong option on the “thinking and planning” side of your stack — while Seedance2.today continues to focus on the “seeing and rendering” side for AI video.