Qwen Models

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.

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.

Alibaba Qwen 3.6 Max Preview, a sparse mixture-of-experts model with ~1 trillion parameters. Optimized for agentic coding, tool use, and long-context reasoning with an integrated thinking mode that preserves reasoning traces across multi-turn conversations. 262K context window, available via Alibaba Cloud Model Studio API.

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.

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 Qwen3.5. 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 Qwen3.5. 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 image generation and editing, improving over Qwen Image 1.x in Chinese text rendering, instruction following, and complex layouts. Compared with GPT Image, Gemini image models, and Seedream, it is well suited to Chinese posters, e-commerce images, infographics, and iterative visual creation.

Built for image generation and editing, improving over Qwen Image 1.x in Chinese text rendering, instruction following, and complex layouts. Compared with GPT Image, Gemini image models, and Seedream, it is well suited to Chinese posters, e-commerce images, infographics, and iterative visual creation.