Qwen Models

An efficient multimodal workhorse in the Qwen family, with a native million-token context window and strong support for coding assistance, agentic workflows, and visual understanding such as charts. It fits long documents, codebases, high-concurrency applications, and tool-assisted tasks.

The speed-first variant of Alibaba's Wan 3.0 line (early access). It shortens generation latency while retaining high-quality video output, making it a good fit for low-latency previews, batch drafts and fast-iterating short-video workflows. If ultimate visual control matters more than speed, the standard version is a better choice.

The standard video generation model of Alibaba's Wan 3.0 line (early access). It supports text-to-video, image-to-video and multi-modal reference inputs, generating clips up to roughly 30 seconds with synchronized audio in a single pass — suitable for ads, short drama and narrative content. Official release date not yet announced.

Qwen's most capable flagship multimodal reasoning model, built for long-horizon coding, professional work, and multi-stage agent tasks. It accepts text, images, and video, offers a 1M-token context window with up to 128K output, and supports function calling, structured outputs, web search, and a code interpreter. It is best used as a high-quality workhorse for complex tasks rather than for the lowest-cost, lowest-latency batch workloads.

A quality-first image generation and editing model: it supports text-to-image and edits from 1–3 reference images, accepts prompts of up to about 4.5K tokens, and is aimed at dense layouts, fine 10px-scale text, 12 languages, and multiple fonts. Choose it over the standard variant when complex composition and detail fidelity matter more than speed or cost; use the standard variant for a faster, more economical workflow.

The balanced standard tier of Qwen-Image 3.0 for image generation and editing: it supports text-to-image and edits from 1–3 reference images, prompts of up to about 4.5K tokens, up to six outputs, and 2K-class resolution. It fits everyday posters, interfaces, infographics, and repeated creative work; move to Pro when complex layouts and fine text fidelity matter more, and use this tier when speed and cost efficiency are the priority.

Built for text-to-video, with a stronger audio-native workflow than HappyHorse 1.0, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Built for reference-to-video, with a stronger audio-native workflow than HappyHorse 1.0, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Built for image-to-video, with a stronger audio-native workflow than HappyHorse 1.0, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Designed for agentic workloads, coding, and office productivity, with a stronger combined focus on long context, tool calling, and structured output than Qwen3.6. Compared with flagship models such as GPT, Claude, and Gemini, it is a cost-effective alternative for Chinese, coding, and multi-step tool workflows.

Designed for agentic workloads, coding, and office productivity, with a stronger combined focus on long context, tool calling, and structured output than Qwen3.6. Compared with flagship models such as GPT, Claude, and Gemini, it is a cost-effective alternative for Chinese, coding, and multi-step tool workflows.

Built for video editing, with a stronger audio-native workflow than 早期视频模型, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Built for text-to-video, with a stronger audio-native workflow than 早期视频模型, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Built for reference-to-video, with a stronger audio-native workflow than 早期视频模型, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.

Built for image-to-video, with a stronger audio-native workflow than 早期视频模型, generating dialogue, sound effects, and background music in one pass. Compared with Veo, Kling, and Runway, its differentiator is synchronized audiovisual generation and character-consistent workflows for short drama, ads, e-commerce, and brand marketing.