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AI In IndustryTop 10 Best Ux Prototyping Software of 2026
Top 10 Best Ux Prototyping Software ranking covers Figma, Adobe XD, Axure RP and more with feature-by-feature comparison for UX teams.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Figma
Figma component variants with instance propagation keep prototypes, specs, and design system docs consistent.
Built for fits when product teams need interactive UX prototypes linked to governed components and API-ready design assets..
Adobe XD
Editor pickXD Prototype mode with hotspots and transitions for clickable, stateful user journeys.
Built for fits when product teams need interactive prototypes and review loops without heavy enterprise governance..
Axure RP
Editor pickDynamic panel states plus variables enable conditional, stateful interaction logic inside prototypes.
Built for fits when teams need interaction-accurate prototypes with reusable components, and external integration automation is minimal..
Related reading
Comparison Table
This comparison table evaluates Ux prototyping tools across integration depth, focusing on how each product connects to design systems, workflows, and external services via API and automation. It also contrasts the data model and schema choices for prototypes and assets, then maps each platform’s admin and governance controls, including RBAC, audit logs, and provisioning. The goal is to show tradeoffs in configuration and extensibility, plus practical implications for throughput when collaboration and iteration scale.
Figma
UI prototypingBrowser-first UI prototyping with interactive components, design tokens, auto-layout, and collaboration features that support structured handoff workflows and API-driven integrations.
Figma component variants with instance propagation keep prototypes, specs, and design system docs consistent.
Figma’s integration depth includes native collaboration, file linking, and design system utilities that map components to documentation. The data model centers on frames, components, and variants, with instances referencing a single component definition to propagate updates predictably. Prototyping uses interaction definitions tied to component states and frame navigation, which improves traceability from UI structure to behavior. Automation and extensibility include the Figma REST API for reading files, assets, and meta data plus webhooks for event-driven workflows.
A key tradeoff is that Figma’s automation and provisioning surface is strongest for design assets and metadata, while real build-time integration still requires external engineering glue. Teams that need to sync tokens, component properties, and usage analytics often use the API plus webhooks to keep downstream systems aligned. A common usage situation pairs design system governance with automated asset export into engineering pipelines. Another common situation uses prototype interaction logic as a review artifact for stakeholder signoff.
- +Component variants propagate changes across prototypes and documentation
- +REST API and webhooks support event-driven design workflows
- +Design-to-prototype interaction mapping keeps behavior tied to structure
- +Role-based access and team workspaces enable controlled collaboration
- –Automation often needs external services for end-to-end engineering sync
- –Large files can slow iteration when many collaborators edit simultaneously
Design systems teams
Govern components with variant-driven prototyping
Fewer inconsistencies during updates
Product UX designers
Prototype flows for stakeholder review
Faster review and iteration
Show 2 more scenarios
Design ops automation owners
Sync assets through API and webhooks
Lower manual handoff effort
REST reads file structure and webhooks trigger downstream export or validation.
Platform and admin governance
Control access and audit collaboration
Tighter governance across teams
Administrative configuration supports permissions management and traceable activity patterns.
Best for: Fits when product teams need interactive UX prototypes linked to governed components and API-ready design assets.
More related reading
Adobe XD
UI prototypingComponent-based UI design and prototyping workflow with integration into Adobe ecosystem and project structures that support extensibility through Adobe tooling.
XD Prototype mode with hotspots and transitions for clickable, stateful user journeys.
Adobe XD supports interactive prototypes using artboards, states, and transitions, plus components for reuse across screens. The handoff path includes specs-style exports and design assets that can align with other Adobe workflows, which helps teams keep intent intact during review cycles. Stakeholder review centers on shareable prototypes where comments attach to the design context, and this reduces the back-and-forth common in static screenshots.
A tradeoff appears in automation and governance controls. Adobe XD’s extensibility is primarily through the XD ecosystem and available integrations, while it lacks a rich administrative layer with RBAC, provisioning, and audit log visibility for enterprise governance. Adobe XD fits situations where prototypes move through lightweight review steps, but it is less suited for organizations needing schema-driven data models or high-throughput API provisioning across multiple teams.
- +Interactive prototypes with artboards, hotspots, and transitions
- +Components and states support consistent reuse across screens
- +Shareable prototype links enable contextual stakeholder feedback
- +Export workflow supports handoff of design assets
- –Limited automation surface compared with API-first workflow tools
- –Governance features like RBAC, provisioning, and audit logs are not enterprise-grade
- –Extensibility depends on third-party integrations rather than a stable first-party schema
Product design teams
Prototype onboarding flows for user testing
Faster iteration on UX steps
UX designers
Maintain component libraries for screens
Consistent UI across prototypes
Show 1 more scenario
Design ops teams
Standardize handoff assets
Lower handoff rework
Exports help keep design assets aligned during handoff, reducing rework from mismatched specs.
Best for: Fits when product teams need interactive prototypes and review loops without heavy enterprise governance.
Axure RP
spec prototypingWireframe and interaction prototyping tool that generates interactive specs, supports reusable components, and enables script-based customization for detailed UX behavior.
Dynamic panel states plus variables enable conditional, stateful interaction logic inside prototypes.
Axure RP delivers page-based prototyping with a data model for variables, dynamic panels, and event-driven logic that can represent user journeys and UI states. It supports reusable components and shared libraries so teams can apply interaction patterns across a design system. Publish can generate shareable prototypes and interaction assets for stakeholder review without building a standalone app.
A tradeoff appears in automation and API depth. Axure RP can script interactions inside prototypes, but it does not provide the same breadth of admin, RBAC, and external system automation surfaces found in enterprise workflow tools. Axure RP fits teams that need high-fidelity interaction logic for product validation and usability testing, while accepting lighter governance for integrations.
- +Stateful dynamic panels model complex UI behavior and transitions
- +Reusable components and libraries reduce duplication across large prototypes
- +Conditional interactions and variables support logic beyond static wireframes
- –External API surface is limited for system-to-system automation
- –Admin and RBAC controls are not designed for enterprise governance
Product UX teams
Prototype multi-step flows with UI states
Stakeholders review real decision paths
Design systems owners
Standardize component behaviors
Reduced inconsistencies across screens
Show 1 more scenario
UX research coordinators
Run usability tests on prototypes
Faster iteration from feedback
Clickable interactions and event logic replicate user journeys for moderated testing.
Best for: Fits when teams need interaction-accurate prototypes with reusable components, and external integration automation is minimal.
Proto.io
no-code prototypingNo-code UX prototyping focused on interaction states and responsive previews with project sharing workflows and import/export support for design assets.
Proto.io variable and state mapping enables data-driven interactions across screens with repeatable configuration.
Proto.io supports UX prototyping with component libraries, stateful interactions, and responsive behaviors built from a structured design workspace. It distinguishes itself with an integration-focused configuration model for dynamic content, reusable variables, and cross-screen logic.
Automation and extensibility are shaped around an API surface for embedding and data-driven behaviors, plus editor-time configuration that keeps prototypes maintainable across iterations. Admin and governance capabilities center on team collaboration controls and versioned project management rather than pure design authoring exports.
- +Reusable components and variables reduce duplication across large prototypes
- +Data-driven screens map inputs into interactive states
- +API-oriented embedding supports prototype delivery inside external apps
- +Project organization supports iteration across multiple design cycles
- –Complex workflows require careful schema-like variable planning
- –Automation coverage can feel limited for multi-system orchestration
- –Admin governance controls are less granular than enterprise workflow suites
- –API usage for custom logic adds integration overhead
Best for: Fits when teams need data-driven UX prototypes with an integration-friendly configuration model and controlled collaboration.
Justinmind
interaction prototypingInteraction-driven prototyping with component libraries and dynamic content rules that support responsive behaviors and validation-oriented flows.
Interactive state and event logic for building behavior-rich prototypes that mimic real UI navigation
Justinmind is a UX prototyping tool that turns interactive flows into testable screens and device-like behaviors. It supports component-driven UI building, state logic, and reusable interaction patterns for high-fidelity prototypes.
Integration depth is mainly exercised through export targets, data inputs for prototype screens, and workflow handoff rather than a deep runtime API model. Automation and extensibility are driven by configuration of interactions and components, with limited visibility into an external automation and API surface for provisioning and governance.
- +Component reuse speeds interaction consistency across multiple prototype screens
- +State and interaction logic supports realistic user flow testing
- +Prototype exports support stakeholder review without requiring environment access
- +Data-driven prototype inputs can reduce manual recreation for form screens
- –External API surface for automation and provisioning is not a documented core capability
- –Schema and data model extensibility for integrations is limited
- –Admin and governance controls like RBAC and audit logs are not central in published workflows
- –Throughput for large prototype systems depends on manual structure management
Best for: Fits when teams need interactive, logic-heavy UX prototypes with consistent components, plus low-friction review handoff.
Sketch
desktop prototypingDesktop UI design and prototype creation with component libraries, symbol-based systems, and plugin extensibility for automation around design assets and styles.
Symbols and components with interaction wiring provide consistent prototype behavior across shared UI structures.
Sketch is a UX prototyping tool used for interface design and interaction previews. Its integration depth centers on Apple-centric workflows, file-based project structures, and plugin extensibility for automation hooks.
Sketch’s data model is document and layer driven, which shapes how components, symbols, and interactions map into exportable prototypes. API surface is primarily via plugins, so automation and governance depend on plugin availability and external process orchestration.
- +Plugin system supports automation of design-to-prototype routines
- +Symbol and component model keeps interaction definitions consistent
- +Layer and style structure improves repeatable prototype exports
- +Apple-native environment aligns with design teams using macOS
- –API automation is plugin-centric rather than schema-driven
- –Hard governance controls like RBAC and audit logging are limited
- –External system sync relies on exports and workflow scripts
- –Dataset-level traceability across prototypes is not first-class
Best for: Fits when design teams need plugin-based extensibility for prototype generation and export workflows.
InVision Studio
historical prototypingFormerly offered interactive prototyping with design-to-prototype workflows and collaboration features, with current functionality routed through related InVision offerings.
Component states and interaction rules keep prototype behavior consistent across revisions.
InVision Studio targets UX prototyping with a design-to-prototype workflow built around components and interactive states. It supports collaboration features like commenting and versioned asset management, which helps teams iterate on prototypes without constant rework.
Integration depth is primarily mediated through InVision’s ecosystem rather than a standalone automation-native API surface. The data model centers on design assets, artboards, and interaction mappings, which limits schema-level extensibility compared with API-first prototyping tools.
- +Component-driven interaction mapping reduces repetitive prototype work
- +Tight handoff into InVision prototype viewing and feedback flows
- +Commenting and asset management support iterative team review
- +Deterministic prototype behavior from explicit states and links
- –Automation and API surface are constrained by ecosystem coupling
- –Data model offers limited external schema and provisioning controls
- –Admin governance lacks granular RBAC and audit log visibility
- –Extensibility depends more on workflow integration than scripting
Best for: Fits when teams need component-based interactive prototypes with structured review and minimal external automation.
Marvel
light prototypingLightweight prototyping tool that supports screen-to-screen interactions and sharing links for review workflows.
API-driven provisioning plus RBAC and audit log coverage for prototype libraries shared across teams.
Marvel targets UX prototype workflows with integration depth across design and developer handoff. It supports versioned assets, components, and interactive behavior so teams can validate flows with stakeholders.
Marvel adds an API and automation hooks that enable schema-aligned data syncing, provisioning, and environment-specific configuration. Governance features like RBAC, audit logging, and export controls help maintain control as prototype libraries scale across teams.
- +Interactive prototypes with reusable components and versioned asset history
- +Documented API supports programmatic creation, updates, and synchronization
- +Automation hooks help run provisioning and configuration across environments
- +RBAC with audit logs supports controlled sharing of prototype libraries
- +Export and handoff options reduce manual steps during review cycles
- –Automation surface can require deeper schema mapping for complex organizations
- –Admin governance controls may not cover every workflow variant teams need
- –High-volume prototype generation can demand careful rate and throughput planning
- –Extensibility relies on API patterns that need engineering effort to standardize
- –Data model customization is limited when teams need bespoke schema fields
Best for: Fits when design teams need API-driven prototype provisioning, governed collaboration, and controlled asset reuse.
Origami Studio
model-based prototypingPrototyping toolkit built for interactive UI models with strong geometry and responsiveness controls for rapid exploration.
Schema-based data binding that drives interaction state from variables tied to a defined data model.
Origami Studio generates UX prototypes from design system data and keeps interactions tied to a structured data model. Origami provides an authoring workflow for screens, components, and variables, then exports prototypes that can read from schemas for repeatable interaction testing.
Integration depth comes from extensibility through configuration, reusable components, and automation hooks that connect prototype state to external logic. Governance depends on workspace controls for managing contributors, access boundaries, and changes across prototype assets.
- +Data model links prototype state to schema-defined variables and interactions
- +Reusable components reduce duplication across flows and prototype variants
- +Automation hooks support repeatable generation of prototype artifacts
- +Extensibility options support integration of external logic into interactions
- +Workspace controls provide access boundaries for prototype authors and reviewers
- –Automation surface can require schema discipline to avoid brittle interactions
- –Complex state flows can increase authoring overhead versus simpler tools
- –Integration patterns may demand custom setup for nonstandard data sources
- –Admin governance controls can be limited for fine-grained operational reporting
- –Prototype performance depends on data binding and interaction graph size
Best for: Fits when teams need schema-driven UX prototyping with automation and governed collaboration across shared assets.
Framer
code-adjacent prototypingUI prototyping and web-rendered interaction previews with code-friendly structure for syncing components and behaviors into production-like prototypes.
Real-time preview tied to deployable web rendering for interaction fidelity during prototyping.
Framer fits teams that want UX prototyping tied closely to a published web experience. It supports component-driven pages, real-time preview, and handoff through shareable links.
Integration depth is strongest around web delivery and embed workflows, not around a separate prototype data model. Extensibility is primarily front-end oriented through code and UI integrations rather than a formal provisioning layer for prototype states and schemas.
- +Live preview matches published output through real web rendering
- +Component and variant patterns keep prototype structure maintainable
- +Embed and web integration workflows support iterative stakeholder review
- +Front-end extensibility enables custom interactions with code
- –No formal RBAC or workspace governance controls for prototype assets
- –Limited evidence of audit logs for prototype edits and publishes
- –Prototype data model and schema automation remain minimal
- –Automation and API surface for prototype state management is limited
Best for: Fits when teams need web-accurate UX prototypes with frequent stakeholder reviews and light automation requirements.
How to Choose the Right Ux Prototyping Software
This buyer’s guide covers how UX prototyping tools fit into real product workflows for teams using Figma, Adobe XD, Axure RP, Proto.io, Justinmind, Sketch, InVision Studio, Marvel, Origami Studio, and Framer.
It focuses on integration depth, the underlying data model, automation and API surface, and admin and governance controls. Each section connects those evaluation axes to concrete capabilities like Figma component variants, Marvel API-driven provisioning, and Origami Studio schema-based data binding.
Integration, data-model discipline, and governance controls
Different prototyping tools expose different integration surfaces, which affects whether prototypes can be generated, updated, or synchronized by external systems. Figma and Marvel provide event-driven and API-oriented workflows, while Sketch and InVision Studio lean on plugin or ecosystem mediation.
The data model also determines how repeatable behavior stays across revisions. Origami Studio ties interaction state to schema-defined variables, and Proto.io uses variable and state mapping that behaves like an editor-time configuration model.
API, webhooks, and automation hooks for prototype creation and sync
Marvel provides a documented API plus automation hooks for programmatic creation, updates, and synchronization of prototype libraries. Figma includes REST API and webhooks to support event-driven design workflows, which enables tighter external integration than tooling that relies on export-only handoff.
Schema-like data model for interaction state and variables
Origami Studio binds prototype interaction state to schema-defined variables so behavior remains driven by an explicit data model. Proto.io similarly uses variable and state mapping to drive data-driven interactions across screens with repeatable configuration.
Component and variant propagation that preserves UI structure across prototypes
Figma component variants propagate changes across prototypes and documentation so behavior stays aligned with governed component structure. Sketch uses symbols and components with interaction wiring to keep shared UI structures consistent across exported prototypes.
Conditional logic primitives for stateful interaction modeling
Axure RP models behavior with dynamic panel states plus variables for conditional interactions that mirror product rules. Justinmind supports interaction-driven state logic with reusable interaction patterns to produce behavior-rich, device-like flow testing.
Governance controls for collaboration at scale
Marvel includes RBAC with audit logs and export controls to keep shared prototype libraries controlled across teams. Figma also supports role-based access and team workspaces for controlled collaboration, while Framer and XD limit formal governance and RBAC depth in published workflows.
Extensibility surface that matches the integration goal
Sketch relies on plugin extensibility where automation centers on design assets and styles through plugins rather than a schema-driven provisioning layer. Proto.io supports API-oriented embedding for prototype delivery inside external apps, but complex orchestration may require custom setup and careful variable planning.
Pick a tool based on integration depth, data-model fit, and operational governance needs
Start by matching the required integration depth to the tool’s exposed automation and API surface. Figma and Marvel fit teams needing REST API and webhooks or documented API-driven provisioning, while Justinmind and Axure RP fit teams that prioritize interaction accuracy and reusable logic with limited external automation.
Next align the data model to the team’s prototype input strategy. Origami Studio and Proto.io support schema-like variable binding, while Adobe XD and Framer focus more on authoring and web-rendered preview rather than a formal runtime data model.
Define the external systems that must create or update prototypes
If prototypes must be created or synchronized by external systems, Marvel and Figma are the most directly aligned tools because Marvel exposes a documented API with automation hooks and Figma provides REST API plus webhooks. If only stakeholder review delivery matters, Adobe XD and Axure RP can still fit because they emphasize shareable prototype links and publish outputs rather than system-to-system automation.
Match the interaction data model to how screens get their inputs
If interaction state must be driven by a defined schema, choose Origami Studio for schema-based data binding tied to variables. If data-driven screens can be expressed through repeatable variable and state mapping, Proto.io offers a configuration model built around inputs mapped into interactive states.
Ensure component reuse and propagation match the review and documentation workflow
If the workflow depends on governed component structure across many screens, Figma supports component variants with instance propagation that keeps prototypes and design system docs consistent. If the workflow depends on reusable symbols and interaction wiring during export generation, Sketch provides a consistent model even when automation is plugin-centric.
Validate that the tool’s logic primitives cover required interaction complexity
If conditional and stateful behavior must mirror product rules, Axure RP provides dynamic panel states plus variables for conditional interactions. If the prototype must behave like an interactive flow with state and event logic for realistic navigation, Justinmind supports interaction-driven state and event logic.
Confirm governance depth for teams sharing prototype libraries
For multi-team collaboration with controlled sharing and traceability, prioritize Marvel because it includes RBAC and audit log coverage tied to prototype libraries. For controlled collaboration without enterprise-grade audit depth, Figma still provides role-based access and team workspaces, while Framer’s governance controls are limited.
Choose based on preview fidelity and where web rendering matters
If interaction fidelity must match a published web rendering, Framer provides real-time preview tied to deployable web output. If web rendering is not the priority and the goal is deterministic state and link-based interaction behavior, InVision Studio and Adobe XD provide component states, transitions, and structured review flows.
Which prototyping teams should prioritize which capabilities
UX prototyping teams need different tradeoffs depending on whether prototypes are purely review artifacts or part of an integrated design-to-workflow system. Integration depth and governance matter most when prototype libraries are shared across teams and updated by automation.
Data-model discipline matters most when prototype interactions depend on repeatable variables and structured inputs rather than manually wired interactions.
Product design teams that require API-ready design assets and governed component reuse
Figma fits this segment because component variants propagate changes across prototypes and documentation and because Figma includes REST API and webhooks for event-driven integration. The tool also supports role-based access and team workspaces for controlled collaboration.
Design and platform teams that want API-driven provisioning and governed prototype libraries
Marvel fits organizations that need documented API workflows plus RBAC and audit log coverage for prototype libraries shared across teams. The tool also supports automation hooks for provisioning and environment-specific configuration.
Teams that need schema-driven, data-bound interactions for repeatable testable flows
Origami Studio fits teams that want interaction state driven by schema-defined variables and that need automation hooks for repeatable generation of prototype artifacts. Proto.io fits adjacent needs because variable and state mapping supports data-driven screens with repeatable configuration.
UX teams focused on interaction-accurate logic rather than deep external automation
Axure RP fits teams that need dynamic panel states and variables for conditional logic that mirrors product rules. Justinmind fits teams that need interaction state and event logic for behavior-rich, device-like flow testing with consistent components.
Web-first teams that prioritize deployable preview fidelity over enterprise governance
Framer fits teams that need real-time preview tied to deployable web rendering and component and variant structure for maintainable prototypes. Adobe XD fits teams prioritizing clickable hotspots and transitions with shareable prototype links for stakeholder review without enterprise-grade governance depth.
Where teams commonly misfit prototyping tools to their workflow
Most mismatches happen when the tool’s integration surface and data model do not match the operational model for prototypes. Another frequent issue is governance expectations that exceed what a tool exposes for RBAC and audit log visibility.
Automation and extensibility also get mis-scoped when teams assume external system orchestration works the same way as export-based handoff.
Choosing a tool with limited automation while planning system-to-system prototype synchronization
Teams needing programmatic creation and updates should avoid relying on tools where automation is mainly export workflow or plugin mediation, such as Justinmind and Sketch. Prefer Marvel for documented API-driven provisioning or Figma for REST API and webhooks.
Building data-driven interactions without committing to a variable or schema discipline
Proto.io requires careful variable and schema-like planning for complex workflows, and Origami Studio requires schema discipline to avoid brittle interactions. Teams that cannot commit to structured variables should constrain prototypes to interaction logic instead of schema-driven data binding in Origami Studio and Proto.io.
Expecting enterprise RBAC and audit logging in tools without formal governance depth
Framer and Adobe XD provide review and collaboration features but lack enterprise-grade governance depth like audit log visibility and granular RBAC. Marvel includes RBAC and audit log coverage for prototype libraries, which matches operational governance requirements.
Underestimating how component propagation affects consistency across prototypes and design system docs
If prototypes must stay aligned with governed components and documentation, avoiding weak propagation models matters. Figma’s component variant propagation keeps prototypes, specs, and docs consistent, while tools that center on exports or plugin workflows can drift unless process controls exist.
Relying on web-rendered fidelity when the tool’s strength is deterministic state mapping for interaction behavior
Framer delivers real-time preview tied to deployable web rendering and can be misused when the team needs schema-driven state automation. Choose Axure RP or Proto.io when the requirement is conditional state logic or data-driven interaction state mapping instead of web-accurate rendering.
How We Selected and Ranked These Tools
We evaluated Figma, Adobe XD, Axure RP, Proto.io, Justinmind, Sketch, InVision Studio, Marvel, Origami Studio, and Framer using features, ease of use, and value, with features weighted most heavily at forty percent. Ease of use and value were weighted equally at thirty percent each, so the ranking favored tools that combine integration breadth with operational control depth.
Figma separated itself because its component variants propagate changes across prototypes and documentation and because it includes REST API and webhooks for event-driven design workflows. That combination lifted both the integration and data-model consistency factors, resulting in the highest overall rating and strong features and ease-of-use scores.
Frequently Asked Questions About Ux Prototyping Software
How do Figma and Origami Studio differ in data model support for interaction state?
Which tool is better for requirements-to-prototype logic using conditional interactions?
What integration and API patterns exist for prototype provisioning across teams?
Which tools provide stronger admin controls such as RBAC and audit logging?
How do security and access controls differ between Figma-style collaboration and Marvel-style governance?
What is the practical difference between embedding data-driven interactions in Proto.io and exporting logic to other workflows?
Which tool is best when stakeholders need link-based click-through review with hotspots and transitions?
How do Axure RP and Origami Studio handle reusable components across multiple screens?
What common problem appears when prototype logic must match device-like behavior, and how do tools address it?
Conclusion
After evaluating 10 ai in industry, Figma stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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