VIDU

Vidu Q2 is a text-to-image AI model developed by fal designed to transform descriptive text prompts into single-frame images. As a dedicated text-to-image solution, Vidu Q2 emphasizes efficiency and simplicity by offering static PNG image generation based solely on user-provided text without the complexities of video or multi-modal input. The model is particularly suitable for teams and individuals seeking straightforward, deterministic conversion of creative ideas into visual content.

With its focus on static image creation, Vidu Q2 processes a single text prompt of up to 1500 characters and produces one PNG image per request. The input prompt allows users to detail complex or nuanced scenes, giving significant flexibility for creative direction and precise content visualization. The model does not require or accept reference images or other input modalities, streamlining the prompt-to-image workflow and removing ambiguity from the creative process.

A key feature of Vidu Q2 is the aspect ratio control, which lets users choose between three standard presets: 16:9 (landscape), 9:16 (portrait), and 1:1 (square). These aspect ratios are optimized for popular web, social media, and content creation formats, helping users eliminate guesswork regarding image resolution and ensuring output images are ready for common distribution channels. The deterministic output option, enabled by specifying a random seed, allows for reproducible results, making it possible to iterate or refine visual outputs over time without unpredictable changes.

Technically, the model accepts a JSON object containing the required text prompt (up to 1500 characters), an optional aspect ratio parameter (defaulting to 16:9), and an optional seed for reproducibility. On completion, Vidu Q2 returns a single output image in PNG format, delivered via a URL. The API delivers the image with metadata such as file size, dimensions (width and height), file name, and MIME type, all accessible for integration into workflows or user interfaces.

Vidu Q2 is architected to provide straightforward, reliable image generation without the overhead or complexity associated with video generation models. The focus on single-frame output and lack of reference image requirements aid rapid prototyping, concept visualization, and content workflows that demand predictable structure and efficient process control. The model is well-suited for marketing asset creation, illustrating concepts for presentations or pitch decks, and creating static visual materials for web or print.

Performance-wise, Vidu Q2 offers a balance between simplicity and detail, allowing comprehensive scene descriptions but limiting output to a single image per prompt. The model supports commercial use, making it an option for both internal projects and client-facing deliverables. Users should be aware that Vidu Q2 is positioned among other generators such as Seedream v4.5, Hunyuan v3, and Recraft V3, which are suited to different requirements for very high-volume pipelines. Vidu Q2, in contrast, chooses a streamlined offering targeted at users who value a simplified, predictable pathway from text prompt to visual asset.

Overall, Vidu Q2 is best leveraged by creative teams, marketers, and developers looking to rapidly prototype or create static image assets directly from detailed text instructions. Its technical design and operational simplicity make it an effective tool for bringing ideas to life without the complexity or distraction of additional modalities.