flux-2/pro/text-to-image
Create reliable, studio-grade visuals with precise color and layout control.
Vidu Q2: Precision Image-to-Image Generator with 4K Output on playground and API | RunComfy
vidu/q2/reference-to-image
Transform reference images into high-quality 4K visuals with precise editing, consistent styles, and fast, production-ready output for film, design, and advertising workflows.
Introduction to Vidu Q2 Image Generation
Developed by ShengShu Technology, Vidu Q2 is a cutting-edge image-to-image model built for creators, designers, and production teams who need consistent, high-quality visuals at incredible speed. Vidu Q2 delivers professional-level editing, reference-based generation, and 4K output with precision and efficiency, making it ideal for film, advertising, and creative media workflows. For developers, Vidu Q2 on RunComfy can be used both in the browser and via an HTTP API, so you don’t need to host or scale the model yourself.
Creative Image Examples Using Vidu Q2
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Frequently Asked Questions
What kind of license does Vidu Q2 image-to-image use, and does RunComfy change it?
Vidu Q2 image-to-image is governed by its original license from ShengShu Technology, often aligned with permissive Open RAIL or similar frameworks allowing research and possible commercial use under stated conditions. RunComfy simply provides API and cloud hosting access — it does not alter or override the model’s original licensing structure. Users must review and adhere to Vidu Q2’s stated license before selling or distributing generated content.
What are the performance considerations of Vidu Q2 image-to-image on RunComfy?
Vidu Q2 image-to-image operates on cloud-hosted GPUs managed by RunComfy, offering low latency (around 3–6 seconds for 1080p) and stable concurrency through automatic GPU scaling. RunComfy manages GPU load balancing so users can run multiple concurrent generations without setup. Local execution isn’t supported due to high hardware demands.
Are there any technical limitations when using Vidu Q2 image-to-image via the RunComfy Playground or API?
Yes, Vidu Q2 image-to-image supports outputs up to 4K resolution, though 1080p is free-tier optimized. Each prompt is limited to roughly 512 tokens, and reference inputs via ControlNet or IP-Adapter are capped at four. Aspect ratios follow 1:1, 16:9, and 9:16 presets to ensure stability across generations.
How can I transition from testing Vidu Q2 image-to-image in RunComfy Playground to a production setup?
You can prototype in the RunComfy Playground (https://www.runcomfy.com/playground) using Vidu Q2 image-to-image, then integrate your workflow via the RunComfy API. The API mirrors playground parameters for inputs, references, and post-processing options. For production use, you’ll need to purchase usd credits, authenticate with your RunComfy API key, and adjust concurrency or callback URLs for automated processing.
What makes Vidu Q2 image-to-image different from Vidu Q1 or other competitors?
Vidu Q2 image-to-image vastly improves consistency, handling multiple references with refined spatial and identity control. It’s up to 2× faster than Vidu Q1 and handles both text-to-image and full-image editing in the same unified architecture. This makes it reliable for professional pipelines across advertising, animation, and concept art where visual continuity is critical.
What are the GPU infrastructure details behind Vidu Q2 image-to-image on RunComfy?
RunComfy runs Vidu Q2 image-to-image entirely on managed GPU clusters in the cloud, eliminating the need for users to provision hardware. Resources are dynamic—users experience minimal latency and autoscaled throughput even at high demand. This managed approach separates inference performance from local computing limitations.
Does using Vidu Q2 image-to-image via RunComfy offer any free trial?
Yes, new RunComfy users receive free trial usd credits that can be used with Vidu Q2 image-to-image for generating outputs up to 1080p. This allows users to evaluate quality and performance before upgrading to paid usage for higher resolution or production-scale workflows.
Where can I get help or report issues related to Vidu Q2 image-to-image on RunComfy?
For support or feedback regarding Vidu Q2 image-to-image usage, integration questions, or GPU availability, you can contact RunComfy directly at hi@runcomfy.com. The platform team assists with both technical troubleshooting and billing inquiries related to usd consumption or API access.