Vidu Q2 Reference-to-Image

Create images with consistent subjects using reference photos and prompts.

"The little devil is looking at the apple on the beach and walking around it."

Image 1

Image 2

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Generated

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📄 About Vidu Q2 Reference-to-Image

Vidu Q2 Reference-to-Image is a cutting-edge AI image generation model designed to create visually compelling images by combining user-provided reference images with detailed text prompts. This advanced tool stands out for its ability to maintain consistent subject appearance across multiple generations, making it a powerful solution for creative professionals, designers, marketers, and anyone seeking to produce high-quality, customized visuals. The core technology behind Vidu Q2 Reference-to-Image leverages state-of-the-art machine learning algorithms that analyze reference images, extract key visual features, and intelligently blend these with the context provided by your prompt. Users can upload between one and ten reference images, ensuring the generated output stays true to the desired subject or theme. Whether you’re aiming to keep a brand mascot’s appearance consistent in various settings, generate character sheets for animation, or simply explore creative visual storytelling, this model delivers exceptional results. A highly flexible input schema allows you to craft a detailed prompt of up to 1500 characters, giving you the freedom to specify scenes, emotions, actions, and more. The aspect ratio of the output image can be selected from 16:9 (landscape), 9:16 (portrait), or 1:1 (square), which ensures your images are perfectly suited for social media, print, or web use. For professionals who require reproducibility, an optional random seed parameter is available, enabling you to revisit and regenerate identical outputs if needed. Vidu Q2 Reference-to-Image’s capabilities make it a versatile tool across a range of applications. Designers can ensure product or character consistency across marketing campaigns and collateral. Content creators and illustrators can rapidly generate variations on a theme or character while maintaining visual uniformity. Marketers and branding specialists will appreciate the ability to create on-brand imagery that aligns with their corporate identity. Even educators and storytellers can use this tool to visualize concepts or create educational materials that require recurring visual elements. The platform operates on a pay-as-you-go credit system, allowing users to scale their usage according to project needs without upfront commitments. With a typical generation time of 15–20 seconds, Vidu Q2 Reference-to-Image delivers fast, reliable outputs, supporting both experimentation and professional workflows. In summary, Vidu Q2 Reference-to-Image is an essential AI tool for anyone who values visual consistency, creative flexibility, and high-quality image generation. Its intuitive interface, robust feature set, and advanced reference-to-image capabilities make it a standout solution in the AI-powered image editing landscape.

✨ Key Features

Generates images from prompts while maintaining consistent subject appearance using reference photos.

Supports uploading 1-10 reference images for nuanced control over the generated output.

Flexible prompt input allows up to 1500 characters for detailed scene and style descriptions.

Choose from multiple aspect ratios: 16:9 (landscape), 9:16 (portrait), and 1:1 (square) to suit different platforms.

Optional random seed parameter ensures reproducible image generations for consistent results.

Fast generation time—typically 15-20 seconds per image, enabling rapid iteration and creativity.

Intuitive user interface with support for multiple file uploads and easy prompt customization.

💡 Use Cases

⚡Maintaining character or mascot consistency across marketing and branding materials.

⚡Generating concept art or storyboard panels with a recurring subject in various scenes.

⚡Creating product images with uniform appearance for ecommerce or advertising.

⚡Visualizing creative ideas or narratives for comics, games, or animation projects.

⚡Developing educational resources featuring consistent visual elements or characters.

⚡Enhancing social media posts with branded, on-topic imagery.

⚡Rapidly prototyping design ideas with visual continuity.

🎯 Best For

🎯 Professional designers, marketers, illustrators, content creators, and brand managers seeking consistent, high-quality image generation.

👍 Pros

✓Ensures consistent appearance of subjects across multiple images.

✓Highly customizable with detailed prompt and multiple reference image support.

✓Quick image generation supports fast-paced creative workflows.

✓Flexible aspect ratio options for diverse output needs.

✓User-friendly interface suitable for both beginners and professionals.

✓Reproducible results with the optional seed parameter.

⚠️ Considerations

△Requires high-quality reference images for best results.

△Limited to a maximum of 10 reference images per generation.

△Output quality relies on the clarity and relevance of provided prompts.

△Advanced customization may require some experimentation.

📚 How to Use Vidu Q2 Reference-to-Image

Prepare 1 to 10 high-quality reference images representing the subject or style you want to maintain.

Write a detailed text prompt (up to 1500 characters) describing the desired scene, action, or mood.

Upload your reference images using the model interface's multiple file option.

Select your preferred aspect ratio: 16:9 (landscape), 9:16 (portrait), or 1:1 (square).

Optionally, set a random seed if you want reproducible results.

Click generate and review the output image; repeat with adjustments as needed for optimal results.

💡 Pro Tips for Vidu Q2 Reference-to-Image

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Upload Multiple Reference Angles For the most consistent subject rendering, upload 3-5 reference images showing your subject from different angles—front, side, and three-quarter views work best. This helps Vidu Q2 understand depth and form, reducing the chance of distorted features. If you need a single headshot instead, consider AI Headshot Generator for faster portrait-specific results.

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Write Detailed Scene Descriptions Use the full 1500-character prompt limit to specify lighting direction, background elements, camera angle, and mood. Phrases like "soft morning light from the left" or "standing in a modern office lobby" give the model concrete visual anchors. Vague prompts often produce generic compositions, so the more specific you are about setting and action, the better your output will match your vision.

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Match Aspect Ratio to Platform Select 16:9 for YouTube thumbnails and presentations, 9:16 for Instagram Stories and TikTok, and 1:1 for Instagram feed posts or profile images. Choosing the correct aspect ratio upfront saves you from cropping later and ensures your subject remains centered and properly framed. This is especially important when maintaining brand consistency across multiple social channels.

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Use the Seed for Iterative Refinement When you generate an image you like but want to tweak the prompt slightly, note the seed value and reuse it. This locks the composition and subject pose while allowing you to adjust scene details, colors, or accessories. It's a powerful way to explore variations without starting from scratch, particularly useful for client revisions or A/B testing marketing visuals.

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Ensure Reference Photo Quality Blurry, low-resolution, or poorly lit reference images will degrade output quality. Use photos taken in good lighting with sharp focus and minimal motion blur. If your references are inconsistent—different hairstyles, clothing, or expressions—the model may blend features unpredictably. For editing existing images with masks or inpainting, try FLUX 2 Dev Edit instead.

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Test Small Before Scaling Generate one or two test images with different prompt variations before committing to a large batch. This lets you dial in the right tone, composition, and subject fidelity without burning credits. Once you have a winning formula—prompt structure, reference set, and aspect ratio—you can confidently produce a series of consistent images for campaigns, storyboards, or product catalogs.

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Frequently Asked Questions

The model analyzes and extracts visual features from uploaded reference images, ensuring that the key characteristics of the subject are consistently maintained across all generated images, even when the prompt or scene changes.

Yes, you can upload between one and ten reference images. Using multiple images helps the model better understand and replicate the subject’s appearance from different angles or in various contexts, leading to more accurate and consistent outputs.

Vidu Q2 Reference-to-Image supports 16:9 (landscape), 9:16 (portrait), and 1:1 (square) aspect ratios, allowing you to create images tailored for different social media platforms, print, or web use.

Pricing varies by model and is based on a pay-as-you-go credit system, which allows users to only pay for the image generations they use, making it flexible for both occasional and frequent users.

Yes, by setting the random seed parameter, you can ensure that the same prompt and reference images will generate an identical output, making it easy to revisit or adjust previous creations.

Credit pricing varies by model and is displayed on the model page before you generate. Vidu Q2 Reference-to-Image typically costs more per generation than simpler text-to-image models because it processes multiple reference images and performs advanced feature extraction. You only pay for successful generations, and there are no monthly subscription fees—just load credits and use them as needed. If you're running a high-volume project, monitor your credit balance and top up in advance to avoid interruptions. Compare costs with other reference-based models like FLUX 2 Face to Full Portrait to find the best fit for your budget and quality requirements.

Yes, all images generated with paid credits on JAI Portal come with commercial-use rights, meaning you can use them in client work, marketing campaigns, product packaging, social media ads, and any other commercial context. Free trial or promotional credits may have different terms, so always check your account's credit source. You retain full ownership of the output, and there are no royalties or attribution requirements. This makes Vidu Q2 Reference-to-Image ideal for agencies, freelancers, and brands that need consistent, on-brand visuals without licensing headaches. For contract or enterprise use, review JAI Portal's terms or contact support for custom agreements.

Vidu Q2 Reference-to-Image generates images in standard web-friendly formats, typically JPEG or PNG, depending on the model's output configuration. Resolution is determined by the selected aspect ratio and the model's native output size—most generations are high enough for web, social media, and standard print use, but may not reach ultra-high-resolution requirements for large-format printing. If you need specific format conversions or higher resolutions, you can post-process outputs with upscaling tools or use models like Qwen Image 2 Pro Edit that support advanced editing and refinement. Always download and inspect your output to confirm it meets your project specs.

JAI Portal offers API access for many models, allowing you to integrate image generation into your own applications, batch workflows, or automated pipelines. API usage still consumes credits on a pay-as-you-go basis, and you'll need to authenticate with an API key from your account dashboard. This is particularly useful for agencies running large campaigns, SaaS platforms embedding AI image generation, or content teams producing hundreds of variations. Check the model's API documentation or contact JAI Portal support to confirm Vidu Q2 Reference-to-Image is available via API and to get code examples. Batch processing can significantly speed up production when you have a consistent prompt and reference set.

First, review your reference images—ensure they're clear, well-lit, and all depict the same subject. Inconsistent references confuse the model. Next, refine your prompt to be more specific about the subject's key features and the desired scene. If results are still off, try reducing the number of reference images to 2-3 of the highest quality, or experiment with different aspect ratios. You can also set a seed and iterate on the prompt while keeping the visual composition stable. If the model struggles with a particular style or subject type, consider testing alternatives like Nano Banana 2 Pro Edit or Bytedance Seedream v5 Lite Edit to see which handles your use case better.

⚖️ How Vidu Q2 Reference-to-Image Compares

Vidu Q2 Reference-to-Image excels when you need to maintain a consistent subject—such as a brand mascot, product, or character—across multiple scenes and compositions. Unlike general-purpose editing tools like OpenAI GPT Image 2 Edit or FLUX 2 Dev Edit, which focus on modifying existing images with masks or inpainting, Vidu Q2 generates entirely new images from scratch using reference photos as a visual anchor. This makes it ideal for creative storytelling, concept art, and branding work where you want the same character or object in different settings. If your goal is to transform a single face into a polished portrait, FLUX 2 Face to Full Portrait is faster and more specialized. For advanced editing workflows that require precise control over specific regions, Qwen Image 2 Pro Edit offers robust inpainting and refinement options. Choose Vidu Q2 when you have 2-10 reference images and need fast, consistent generation with flexible aspect ratios and detailed prompt control. It strikes a balance between ease of use and output quality, making it a strong choice for marketers, designers, and content creators who value visual continuity. Explore JAI Portal's side-by-side compare view or sign up to test Vidu Q2 alongside other reference-based and editing models with pay-as-you-go credits.