Google Stitch vs Tencent Ardot: AI Ideation or a Full Design Workspace?

Quick verdict

Google Stitch and Tencent Ardot both turn natural language into interface designs, but they solve different parts of the workflow.

Stitch is an AI-first starting point. Open the web app, describe a screen, and get a direction in seconds. It is built for fast exploration before a formal design exists.
Ardot is closer to a “Figma + AI” workspace. It combines text-to-UI with vector editing, auto layout, components, variables, team libraries, collaboration, permissions, and design-to-code handoff.

If you only need to validate a direction, Stitch is lighter. If you need to move a design into a team workflow and development handoff, Ardot is more complete. The two can also work as a relay.

What each tool is

Google Stitch is Google Labs’ AI UI design tool. Its core workflow is turning text or images into interface designs, then carrying the design context forward through DESIGN.md, MCP, and Agent Skills. It is primarily a web tool and is a strong fit for rapid exploration and concept validation.

Tencent Ardot is Tencent Design’s AI-native design platform, available on macOS, Windows, and the web. It puts AI generation inside a full design editor. Official capabilities include text-to-UI, image-to-design, Figma .fig import, vector editing, auto layout, component variants, design variables, team libraries, comments, permissions, audit logs, and developer handoff with annotations and code snippets.

Core differences

Dimension	Google Stitch	Tencent Ardot
Core positioning	AI UI generation and exploration	AI-native design workspace
Platforms	Web	macOS / Windows / Web
Text-to-UI	Strong, prompt-first	Strong, built into a full editor
Image-to-design	Supported	Supported, with deeper editing afterward
Figma workflow	Fast mode can export to Figma for refinement; not a `.fig` import entry	`.fig` import preserves layout, styles, and components
Vector editing / auto layout	Basic	Full-featured
Design systems	DESIGN.md and design context	Components, variants, variables, modes, team libraries
Team collaboration / permissions / audit	Limited	Full-featured
Design-to-code	HTML export, convertible to React/Vue and other formats; DESIGN.md, MCP/CLI/Skills	Annotations, CSS/iOS/Android snippets, MCP, CodeBuddy (React/Vue/mini programs)
Pricing	Currently free	Starter free; Pro/Team/Enterprise limited-time free + AI Credits
Mainland China access	Depends on Google service availability	Tencent Cloud product; more direct for teams in mainland China

AI generation: both can draft, but the emphasis differs

Stitch’s advantage is that it removes a step. You do not need to learn a design tool first. A sentence produces a complete screen, and follow-up prompts adjust layout, color, and information density. It is a natural fit for product managers, founders, developers, and designers who want to compare several visual directions quickly.

Stitch also offers several Design Modes: Thinking with 3 Pro for complex logic and production candidates, Redesign for applying a specific aesthetic to an existing interface, and Fast for rapid wireframing and Figma exports. It can generate one to five variations at a time and uses a Creative Range to control how far each option departs from the current design.

Ardot also supports text-to-UI and image-to-design, but its AI behaves more like an assistant inside an editor. After generation, you can keep working with vector tools, auto layout, components, and variables. Official features also include AI image generation, icon generation, link-to-UI, and AI search. For teams that need to refine a generated screen, keeping everything in one workspace reduces tool switching.

Editing and design systems

This is the biggest difference between the two products.

Stitch focuses on generation and design context. Through DESIGN.md, it can capture color, typography, spacing, and component rules in a format that AI tools can read. It can also turn a screen into a scrollable, interactive prototype to check hover states and other interactions. That makes it useful for expressing design intent, but it is not a traditional full design editor.

Ardot offers editing closer to Figma: vector grids, boolean operations, 3D rotation, auto layout, component variants, component properties, design variables, and multi-theme modes. Teams can publish components, styles, and variables to a shared library so multiple screens stay on the same system. For teams maintaining a design system over time, those capabilities matter more than a single generated mockup.

Figma migration and team collaboration

Ardot officially supports importing .fig files while preserving layout, styles, and components. Teams with an existing Figma workflow can treat Ardot as an AI-enabled workspace rather than starting from zero.

Stitch’s Fast mode can export wireframes to Figma for refinement, but its primary entry points are text, images, and Code-to-Design workflows, not .fig import. It is better suited to the direction-exploration stage than to replacing an existing design-file workflow.

On collaboration, Ardot supports real-time comments, annotations, version comparison, a permission center, and audit logs. Stitch is more individual-oriented and does not carry the same team governance responsibilities. If your team needs design reviews, asset handoff, and permission control, Ardot is more complete.

Design-to-code and MCP

Both products are moving toward agent workflows, but from different directions.

Stitch uses MCP, the CLI, and Agent Skills to pass design context to tools such as Claude Code, Cursor, Gemini CLI, and Antigravity. Stitch’s HTML output can then be converted by LLMs into React, Vue, Angular, Jetpack Compose, Flutter, or SwiftUI. Its strength is turning prompts and design context into executable tasks for prompt-centric teams.

Ardot provides developer annotations, component variant inspection, and CSS, iOS, and Android code snippets. Its official MCP documentation lists tools for projects, canvas state, design variables, and component libraries, and supports MCP clients such as CodeBuddy, Cursor, and Claude Code. The official documentation also describes sending designs through MCP to CodeBuddy to generate React, Vue, or mini-program code. It emphasizes the design file itself as a deliverable, which fits design-team-led workflows.

Pricing and availability

As of October 28, 2026:

Stitch is currently free to use, but Google may change pricing and regional availability.
Ardot has a free Starter plan. Pro, Team, and Enterprise are currently limited-time free and use AI Credits for AI features. As a team grows, seats and credits become the real cost.

On availability, Ardot is a Tencent Cloud product and is generally more direct for teams in mainland China. Stitch depends on a Google account and may be limited in some regions or network environments. Check each vendor’s current terms before standardizing on either tool.

How to choose

Choose Google Stitch when:

You do not have a design yet and want to compare several UI directions quickly
You do not want to learn a full design tool first
You value prompt-first workflows, DESIGN.md, and the Google ecosystem
You mainly need concept validation rather than long-term design-system maintenance

Choose Tencent Ardot when:

You need a design workspace with real editing depth
Your team already has Figma files and wants a smoother migration path
You need components, variables, shared libraries, permissions, and audit logs
You are working with a team in mainland China and care about access reliability
You want designs to flow directly into developer handoff and MCP workflows

A combined workflow

The most practical approach is not to pick one forever, but to use each at the right stage:

Use Stitch to generate two or three screen directions and settle the information structure and visual tone.
Bring the chosen direction into Ardot for components, variables, responsive details, and team review.
Hand off through Ardot annotations, code snippets, or MCP, or continue with Stitch’s DESIGN.md and Skills for a coding agent.

This keeps Stitch’s drafting speed while using Ardot’s editing and collaboration depth.

Bottom line

Stitch and Ardot both belong in an AI design toolkit, but they are not the same kind of tool. Stitch is strongest from zero to direction; Ardot is strongest from direction to deliverable design. If you only need exploration, Stitch is enough. If design needs to become part of a team process, Ardot is more complete. Using them as a relay is usually more effective than choosing one in isolation.