
Exploring creative possibilities: A visual guide to Amazon Nova Canvas

Compelling AI-generated images start with well-crafted prompts… Each image is paired with the prompt and parameters that generated it, providing a practical starting point for your own AI-driven creativity… Whether you’re crafting specific types of images, optimizing workflows, or simply seek…
Compelling AI-generated images start with well-crafted prompts. In this follow-up to our Amazon Nova Canvas Prompt Engineering Guide, we showcase a curated gallery of visuals generated by Nova Canvas—categorized by real-world use cases—from marketing and product visualization to concept art and design exploration.
Each image is paired with the prompt and parameters that generated it, providing a practical starting point for your own AI-driven creativity. Whether you’re crafting specific types of images, optimizing workflows, or simply seeking inspiration, this guide will help you unlock the full potential of Amazon Nova Canvas.
Solution overview
Getting started with Nova Canvas is straightforward. You can access the model through the Image Playground on the AWS Management Console for Amazon Bedrock, or through APIs. For detailed setup instructions, including account requirements and necessary permissions, visit our documentation on Creative content generation with Amazon Nova. Our previous post on prompt engineering best practices provides comprehensive guidance on crafting effective prompts.
A visual guide to Amazon Nova Canvas
In this gallery, we showcase a diverse range of images and the prompts used to generate them, highlighting how Amazon Nova Canvas adapts to various use cases—from marketing and product design to storytelling and concept art.
All images that follow were generated using Nova Canvas at a 1280x720px resolution with a CFG scale of 6.5, seed of 0, and the Premium setting for image quality. This resolution also matches the image dimensions expected by Nova Reel, allowing you to take these images into Amazon Nova Reel to experiment with video generation.
Landscapes
Character portraits
Fashion photography
Product photography
Food photography
Architectural design
Concept art
Illustration
Graphic design
Conclusion
The examples showcased here are just the beginning of what’s possible with Amazon Nova Canvas. For even greater control, you can guide generations with reference images, use custom color palettes, or make precise edits—such as swapping backgrounds or refining details— with simple inputs. Plus, with built-in safeguards such as watermarking and content moderation, Nova Canvas offers a responsible and secure creative experience. Whether you’re a professional creator, a marketing team, or an innovator with a vision, Nova Canvas provides the tools to bring your ideas to life.
We invite you to explore these possibilities yourself and discover how Nova Canvas can transform your creative process. Stay tuned for our next installment, where we’ll dive into the exciting world of video generation with Amazon Nova Reel.
Ready to start creating? Visit the Amazon Bedrock console today and bring your ideas to life with Nova Canvas. For more information about features, specifications, and additional examples, explore our documentation on creative content generation with Amazon Nova.
- Creative content generation with Amazon Nova
- Prompting best practices for Amazon Nova content creation models
- Image and video prompt engineering for Amazon Nova Canvas and Amazon Nova Reel
About the authors
Yanyan Zhang is a Senior Generative AI Data Scientist at Amazon Web Services, where she has been working on cutting-edge AI/ML technologies as a Generative AI Specialist, helping customers use generative AI to achieve their desired outcomes. Yanyan graduated from Texas A&M University with a PhD in Electrical Engineering. Outside of work, she loves traveling, working out, and exploring new things.
Kris Schultz has spent over 25 years bringing engaging user experiences to life by combining emerging technologies with world class design. As Sr. Solutions Architect within Amazon AGI, he influences the development of Amazon’s first-party generative AI models. Kris is passionate about empowering users and creators of all types with generative AI tools and knowledge.
Sanju Sunny is a Generative AI Design Technologist with AWS Prototyping & Cloud Engineering (PACE), specializing in strategy, engineering, and customer experience. He collaborates with customers across diverse industries, leveraging Amazon’s customer-obsessed innovation mechanisms to rapidly conceptualize, validate, and prototype innovative products, services, and experiences.
Nitin Eusebius is a Sr. Enterprise Solutions Architect at AWS, experienced in Software Engineering, Enterprise Architecture, and AI/ML. He is deeply passionate about exploring the possibilities of generative AI. He collaborates with customers to help them build well-architected applications on the AWS platform, and is dedicated to solving technology challenges and assisting with their cloud journey.
Author: Yanyan Zhang