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Updated on Apr 7, 2025

Screenshot to Code: Lovable vs v0 vs Bolt in 2025

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During my 20 years as a software developer, I led many front-end teams in developing pages based on designs that were inspired by screenshots. Designs can be transferred to code using AI tools. While expecting a pixel-perfect transfer is wrong in the current state of the tools, they can give developers a foundation to work on. We benchmarked the following tools:

Benchmark results

The outputs were never pixel-perfect. The aim of the benchmark is to determine the solution that can produce output that can reduce front-end developers’ work. Leaders of this benchmark are v0 and Bolt.

v0 and Bolt are the leaders of the screenshot to code benchmark.
Figure 1: Results of the screenshot to code benchmark.

You can see the outputs of the tools in the Outputs section.

Methodology

We used 5 different design pages and a prompt as inputs.

Prompt: Create a pixel-perfect implementation of this UI design.

Metrics

Element count:

  • Total number of boxes/containers

  • Total number of buttons

  • Total number of text elements

  • Total number of images/icons

  • Total number of input fields (if any)

Result: (Elements Correctly Implemented / Total Elements in Original Design)

Methodology:

  1. Quantitative analysis: (%50)

  • Percentage of correctly implemented elements

  1. Qualitative analysis: (%50)

  • Typography style (serif/sans-serif/display)

  • Layout structure

  • Visual elements

  • Basic styling (rounded corners, borders)

  • Color usage

Where: 0 = Wrong/Missing 1 = Close/Similar approach 2 = Correct implementation

Please note that 2 points do not indicate a pixel-perfect implementation but signify that the result is very close to the input.

You can also read our prompt-to-code benchmark with the same tools.

Outputs

Figure 2: Input design.1
Figure 2: Output of the v0.
Figure 4: Output of the Bolt.
Figure 5: Output of the Lovable.

What is the design-to-code process?

Design to code is the process of translating a design mockup or prototype to code that can be implemented by developers. This process involves converting graphical elements, layout structures, interaction designs, and other visual components into HTML, CSS, and possibly JavaScript code.

It is a crucial step in product development, ensuring that the visual and interactive aspects of a product or application are accurately represented in the final implementation. Collaboration between designers and developers is essential to ensure that the design intent is preserved while addressing technical constraints and requirements.

Challenges of converting design to code

The process of turning a prototype into code creates more steps than necessary, taking weeks or months to complete. It can be time-consuming for product teams.

The development process of passing work between product managers, designers, and developers quickly becomes expensive.

The role of AI in design-to-code conversion

AI helps with code generation, making it possible to convert UI design to code quickly and efficiently.

AI coding tools can write code and create responsive design components, which can help developers work faster. They can also review code against potential security issues.

FAQ

What is design tool compatibility and integration?

Design-to-code tools should be compatible with a variety of design tools and platforms, including Figma, Sketch, and Adobe XD. They can turn designs from these tools into an app or a website. Integration with design tools should be seamless, allowing designers to work efficiently and effectively. Design-to-code tools should also be able to handle complex design files and convert them into clean, production-ready code. Compatibility with existing codebases is also crucial, allowing developers to integrate generated code into their existing projects.

What is code generation?

Code generation should be fast and efficient, allowing designers and developers to work quickly and effectively. The generated code should be clean, maintainable, and production-ready, reducing the need for manual coding and debugging. Codes should also be customizable, allowing developers to tailor the code to their specific needs and requirements. Production-ready code should be compatible with a variety of platforms and frameworks, including web, mobile, and desktop.

What are the best practices for a smooth screenshot-to-code process?

Designers and developers should work closely together to ensure that the design intent is preserved while addressing technical constraints and requirements. Designers should use tools that are compatible with code generation tools, making it possible to work efficiently and effectively. Writing clean code helps to understand the code later in more complex projects such as mobile apps. Designers and developers should work together to create a design system that is consistent and maintainable. Designers and developers should also use code components to create interactive elements and complex projects quickly and efficiently.

How does a screenshot-to-code tool work and what to expect from it?

A screenshot-to-code tool transforms your UI designs into implementation by analyzing your interface elements. When you upload a simple app, the system generates a code snippet or code block that represents your design. These tools typically produce functional code that you can further customize.
The process usually begins with a simple app converts mechanism that analyzes your design elements and creates appropriate markup. Many platforms provide a comprehensive set of tools for developers to refine the output, allowing you to get workable code that matches your needs.
Some tools even offer features to store data and copy it to a clipboard for easy integration.
While these solutions aim to streamline the development process, it’s important to remember that they may require adjustments to match your exact specifications, and you might need to check different version options to find the best fit for your project.

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Sedat is a technology and information security leader with experience in software development, web data collection and cybersecurity. Sedat:
- Has ⁠20 years of experience as a white-hat hacker and development guru, with extensive expertise in programming languages and server architectures.
- Is an advisor to C-level executives and board members of corporations with high-traffic and mission-critical technology operations like payment infrastructure.
- ⁠Has extensive business acumen alongside his technical expertise.
Şevval is an AIMultiple industry analyst specializing in AI coding tools, AI agents and quantum technologies.

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