VIDU

Vidu Q2 is a text-to-image AI model developed by fal, designed to transform descriptive text prompts into high-quality static images. With streamlined architecture that exclusively focuses on generating single-frame images, Vidu Q2 eliminates the complexity often associated with video or multimodal generation, providing users with a direct, predictable workflow for visual creation.

Core Capabilities At its foundation, Vidu Q2 ingests text prompts of up to 1500 characters, allowing for detailed scene descriptions and nuanced creative input. Users can specify one of three aspect ratios—16:9, 9:16, or 1:1—which correspond to standard formats widely used in web, social media, and design applications. Vidu delivers its outputs as PNG images accessible via URL, which simplifies integration into digital workflows and downstream processes.

The model features a deterministic generation option through a seed parameter, enabling users to reproduce and iteratively refine outputs—a feature valuable for design teams, marketers, and content creators needing consistency across creative cycles. Each text prompt yields a single static image, ensuring predictability and control over content creation without concerns about multi-frame or animated outputs.

Intended Use Cases and Target Users Vidu Q2 is particularly well-suited for teams and professionals engaged in rapid prototyping, static asset creation for marketing, concept visualization, and workflows that demand straightforward, single-image generation. The model's design accommodates workflows where video generation or multimodal assets are unnecessary or could introduce unwanted complexity.

Suggested use cases, as documented, include:

• Marketing asset creation: Generating campaign images or promotional visuals directly from descriptive copy.
• Concept visualization: Enabling creative professionals to quickly mock up scenes, characters, or environments based on textual descriptions.
• Static content workflows: Supporting digital content creators and designers in producing web-ready or social media visuals aligned to industry-standard aspect ratios.

Technical Details Vidu Q2 requires text input in the form of a prompt (maximum length 1500 characters). No reference images or other modalities are supported or required, underscoring the model’s focus on streamlined text-to-image conversion. Users can further tailor output by selecting one of the three fixed aspect ratios:

• 16:9 (landscape)
• 9:16 (portrait)
• 1:1 (square)

Output images are delivered in PNG format via a URL, and include metadata such as file name, size, width, and height. Each generation call produces a single image, keeping API responses clean and predictable.

A random seed parameter allows for deterministic image generation, which is beneficial for iterative design processes or versioning.

Performance Characteristics Vidu Q2 is positioned as a mid-tier image generator, prioritizing straightforward implementation and simplicity. Its architecture trades advanced or complex features found in video/image models for a focused, single-frame generation pipeline. Prompt handling is efficient; up to 1500 characters per prompt allows for granular scene description without the overhead or ambiguity of multimodal inputs.

Aspect ratio selection is preset, removing the need to manage custom resolutions and making the model well-aligned with the graphic standards of web and social channels. The consistent PNG output format further simplifies downstream use and sharing of generated images.

Limitations and Considerations Vidu Q2 is optimized for static image generation only—no support for video, animation, or advanced image editing is included. The three fixed aspect ratios are designed for broad utility but may not address specialized or custom sizing needs. The model returns only one image per request; batch processing or multi-image responses must be managed at the workflow or application level. The documentation does not detail model strengths related to photorealism, artistic style, or other qualitative aspects of image generation. For high-volume workflows, users should note that Vidu Q2 provides a balance of simplicity and predictability, rather than advanced feature sets.

Best Practices Detail and clarity in prompts are important due to the 1500-character capacity; users should exploit this limit for precise creative control. Selecting the appropriate aspect ratio at generation time ensures immediate usability of assets for their intended publication format.

In summary, Vidu Q2 delivers a focused, efficient single-image creation experience from descriptive text prompts. Its deterministic outputs, flexible prompt handling, and fixed aspect ratios offer creative teams, marketers, and content professionals a clean, practical solution for static visual asset generation.