GITNUXSOFTWARE ADVICE
Art DesignTop 10 Best Ui Ux Designing Software of 2026
Top 10 Ui Ux Designing Software ranked by features for designers. Includes Figma, Adobe XD, and Sketch comparisons and tradeoffs.
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
Design system libraries propagate components and styles across files with consistent IDs and update behavior.
Built for fits when design teams need API-driven workflows plus component-governed UI handoff..
Adobe XD
Editor pickInteractive prototyping with triggers and states across responsive artboards in one document.
Built for fits when teams prototype and hand off UI work inside Creative Cloud workflows..
Sketch
Editor pickSymbols and symbol overrides let teams propagate UI system changes across documents with controlled variants.
Built for fits when UI teams need component reuse automation without heavy enterprise integration overhead..
Related reading
Comparison Table
The comparison table maps Ui and UX design tools across integration depth, including how each product connects to design systems, repositories, and workflow automation. It also compares the underlying data model and schema choices, then documents automation, API surface, extensibility, and provisioning paths that support teams using RBAC, audit log reporting, and governance controls.
Figma
design+APICloud UI design and prototyping platform with component libraries, variables, interactive prototypes, and an integrations API for automation and design-data workflows.
Design system libraries propagate components and styles across files with consistent IDs and update behavior.
Figma’s core data model organizes work into files, pages, frames, components, instances, and variant sets, and it exposes those objects consistently for collaboration and handoff. Design system libraries distribute components and styles across teams, and change control follows design IDs and versioning within files. Integration breadth comes from a plugin architecture for local tooling and a public API for external automation that reads and writes file content and user-generated annotations.
A key tradeoff is that deep data-model automation depends on API scope and object limits, so high-throughput pipelines may need batching and careful pagination. A common usage situation is design system governance where a team automates style extraction, validates component structure, and syncs generated documentation with audit-ready records tied to file history.
- +Component variants and auto-layout encode layout logic in reusable structures
- +Design system libraries distribute styles and components across teams
- +REST API supports file reads, versions, and workflow automation
- +Plugin ecosystem enables custom validators and report generation
- –Complex automation needs object scoping and pagination for high throughput
- –Some advanced governance workflows require external tooling and process alignment
Design system engineers
Automate library compliance checks
Fewer regressions in UI patterns
Product design teams
Collaborate on shared UI specs
Faster review cycles
Show 2 more scenarios
Design operations
Automate documentation generation
Up-to-date system documentation
Plugins and API automation render component inventories and keep specs aligned to source files.
Platform engineering teams
Integrate design artifacts into pipelines
Consistent handoff into builds
External services pull file data via API for token mapping and automated asset exports.
Best for: Fits when design teams need API-driven workflows plus component-governed UI handoff.
More related reading
Adobe XD
desktop editorUI and UX design tooling for wireframes and interactive prototypes with plugin extensibility and design assets export paths into Adobe workflows.
Interactive prototyping with triggers and states across responsive artboards in one document.
Adobe XD fits teams that need quick iteration on screens and prototypes, plus artifact handoff to other Adobe tools. Interactive prototypes support triggers and states across artboards, and responsive resize uses constraints to keep layouts consistent across target sizes. Creative Cloud libraries and assets can be reused across documents, which reduces duplication when teams standardize components. Review tooling supports comments on designs, which helps capture feedback tied to specific screens and interactions.
A key tradeoff is the limited administrative and governance control surface compared with enterprise design systems stored in a centralized schema. Teams that require RBAC, org-wide provisioning, and audit log exports for design artifacts will face gaps. Adobe XD works best when collaboration stays within Creative Cloud workflows and when handoff is managed through export formats for engineering consumption. It is less suited for organizations that want full API-driven lifecycle management of design objects and versions.
- +Interactive prototype states with triggers across artboards
- +Responsive resize uses constraints for layout consistency
- +Creative Cloud asset and library reuse reduces duplication
- +Built-in review comments tied to specific screens
- –Limited admin governance, RBAC, and audit log automation
- –Project file data model lacks schema-based provisioning options
- –Automation depends on exports and Creative Cloud workflows
- –API surface for custom integrations is comparatively narrow
Product designers
Prototype end-to-end flows quickly
Faster feedback cycles
Design systems teams
Standardize components via libraries
Reduced component drift
Show 2 more scenarios
UX research collaborators
Annotate screens during reviews
Clear review trails
Capture comments on specific design surfaces to track issues during iteration.
Front-end engineering teams
Handoff assets and specs
Lower handoff ambiguity
Export visual assets from XD and align implementations to the defined artboard layouts.
Best for: Fits when teams prototype and hand off UI work inside Creative Cloud workflows.
Sketch
plugin automationMac-first UI design tool using symbol libraries and plugin APIs for automation, asset export, and design system maintenance.
Symbols and symbol overrides let teams propagate UI system changes across documents with controlled variants.
Sketch emphasizes a component and symbol-based data model, so teams can define shared UI primitives and update them across screens. Collaboration centers on shared libraries and file conventions, which reduces drift when multiple designers edit the same UI system. Integration depth is strongest through plugins that can read and manipulate the document structure, not through a broad external connector catalog.
The primary tradeoff is that governance and automation depth depends heavily on installed plugins rather than a centralized API-first admin layer. Sketch fits organizations where UI specs and assets flow from designers into downstream handoff steps, with scripting filling automation gaps. A typical fit is a design team standardizing icon sets, tokens, and component variants, then running the same transformations each release cycle.
- +Symbol libraries make component reuse and updates predictable
- +Document scripting and plugins automate repetitive UI transformations
- +File structure supports consistent handoff from design to spec
- –Automation and integration breadth depend on available plugins
- –Central admin, RBAC, and audit logs are limited compared with enterprise suites
- –Throughput can lag on complex files with many nested components
Product design teams
Maintain shared component variants
Fewer manual edits
Design ops leads
Standardize assets with plugins
Repeatable workflows
Show 2 more scenarios
UI engineering handoff teams
Convert design structure to specs
Faster specification cycles
Structured layers and component semantics reduce mapping time when exporting requirements for implementation.
Small design orgs
Prototype component systems quickly
Consistent UI prototypes
Symbol-first authoring helps prototype responsive UI states with reusable patterns.
Best for: Fits when UI teams need component reuse automation without heavy enterprise integration overhead.
Axure RP
spec+prototypeLow to high fidelity UX prototyping and specification authoring with reusable components, page flows, and export targets for documentation and prototypes.
Conditional interactions and dynamic behaviors are configured per widget in Axure’s model, then compiled into prototype output.
Axure RP is a UI and UX design tool focused on spec-ready interaction modeling with reusable components. It includes Axure-specific object and behavior configuration that generates prototype-ready flows directly from the design surface.
Integration depth is limited because its automation and extensibility center on Axure project files, export outputs, and scripted workflows around those artifacts. Governance controls are primarily design-time features like organization of assets and shared libraries, with no clear enterprise RBAC, audit logging, or API-backed provisioning surface.
- +Interaction-driven prototyping with conditional logic on widgets
- +Reusable libraries support consistent components across pages
- +Exports generate prototype artifacts for stakeholder review
- –Data model for UI logic stays proprietary to Axure artifacts
- –Automation relies on export-driven workflows instead of an open API
- –No documented RBAC, audit logs, or admin governance controls
Best for: Fits when small teams need interaction-spec prototypes and reusable components without deep enterprise integration requirements.
Webflow
design to siteVisual design and CMS-backed site builder with design-to-production workflow and automation via APIs and webhook-style integrations.
Webflow CMS with API and webhooks couples content schema to automation triggers for controlled publishing workflows.
Webflow renders UI in a visual editor while generating front end markup from a structured site model. Integration depth centers on external publishing, CMS collections, and custom code hooks that map into Webflow’s content schema.
Automation and extensibility rely on Webflow APIs for content, localization, and webhook-driven workflows rather than built-in multi-step orchestration. Admin governance is handled through workspace roles and project permissions that gate editing and publishing actions across teams.
- +CMS collections map to a concrete data model with field schemas
- +Webflow API supports programmatic content updates and schema-aligned provisioning
- +Webhooks enable automation triggers tied to CMS events and publishing changes
- +Workspace RBAC restricts editor and publisher actions per project roles
- –Data model depth is limited for complex relational schemas and joins
- –Automation surface depends on API and webhooks rather than visual workflow builders
- –Admin audit coverage is constrained compared with enterprise governance suites
Best for: Fits when design teams need schema-based CMS publishing and controlled automation via API and webhooks.
ProtoPie
interactive prototypingInteractive prototype authoring for UX testing with logic blocks and device input simulation plus integration options for embedding and handoff.
Interactive logic that supports variables, conditions, and sensor-driven behaviors for device-tested UX prototypes.
ProtoPie fits teams building UI and UX prototypes that react to real device inputs, not just scripted animations. Its core capability is Prototyping with interactive logic, including variables, conditions, and sensor-driven behaviors that can be tested on mobile hardware.
Integration depth centers on exporting build artifacts for device testing and connecting interactions to external data sources through defined interfaces. Automation and extensibility hinge on how interactions are structured and parameterized so they can be configured and reused across flows.
- +Device-connected interactions support sensor inputs like touch and motion
- +Logic layer supports variables, conditions, and reusable interaction patterns
- +Exports enable stakeholder testing on real mobile and hardware setups
- +Parameterized behaviors improve configuration reuse across prototype variants
- –State and data model discipline is required to avoid tangled interaction logic
- –External data wiring depends on the specific interface available for each integration
- –Governance controls like RBAC and audit logs are not the focus for many teams
- –Throughput for large prototype libraries can require careful project organization
Best for: Fits when product teams need interactive, device-level UX prototypes with configurable logic and repeatable interaction patterns.
InVision
review+sharingDesign collaboration and prototype review tooling with project libraries and integrations for sharing UX artifacts and feedback workflows.
Comment threads on prototype states, tied to iteration history, support structured UI feedback and review traceability.
InVision focuses on UI and UX review workflows built around shared prototypes and design handoff artifacts. It supports projects with role-based access, comment threads, and iteration history tied to specific prototype states.
Team workflows depend on integration with common design and asset pipelines, plus extensibility through developer-facing surfaces and webhooks. Admin governance emphasizes user management, organization structure, and traceability via activity and audit-style records.
- +Prototype comments link feedback to specific screens and prototype states
- +Role-based access supports controlled review across teams
- +Integration paths connect design assets and review workflows
- +Developer surfaces support automation via API calls and webhooks
- +Versioned iteration history helps track design review outcomes
- –Automation surface can require custom schema mapping for complex pipelines
- –Cross-tool data model normalization adds overhead for large design systems
- –Governance reporting granularity can lag audit needs in regulated setups
- –Prototype-to-handoff syncing can break when naming or structure diverge
Best for: Fits when teams need comment-driven prototype review with role-based governance and API-backed workflow automation.
Marvel
rapid prototypingLightweight UX prototyping and design review tool for interactive mockups with collaboration features and export sharing workflows.
Component variants in the design data model that maintain consistency across prototypes and collaborative review.
Marvel is a UI and UX designing workspace focused on component-driven design and handoff workflows. Integration depth centers on collaboration, assets, and design-to-delivery pipelines rather than heavy data engineering.
The data model supports reusable components, variants, and design assets that carry through to prototyping and collaboration. Automation and extensibility rely on configuration options and documented integrations that connect design activity to downstream work.
- +Component and variant data model supports consistent UI behavior across screens
- +Collaboration workflow links design changes to review and iteration cycles
- +Asset reuse reduces drift across related flows and prototypes
- +Integration options connect design artifacts to downstream delivery work
- –Automation surface feels narrower than tools with deeper workflow APIs
- –API surface and schema depth are less suited for custom provisioning
- –Admin and governance controls may not cover advanced enterprise RBAC needs
- –Audit log detail may not match requirements for regulated design governance
Best for: Fits when teams need component-driven UI design and structured handoff without extensive custom data workflows.
Maze
UX testingUX validation and prototype testing tool that supports integration patterns for capturing test inputs and managing study artifacts.
Step-level feedback capture that binds observations to specific tasks inside a UX session.
Maze turns tested UX flows into shareable prototypes and collects experience feedback tied to user interactions. It integrates with common design and research pipelines through project imports, embedding, and developer-facing configuration options.
Maze’s data model links tasks, sessions, and observations to consistent artifacts so automation can target specific steps. Admin governance focuses on workspace control, permissions, and traceability through activity records.
- +Feedback is anchored to tasks and user steps for traceable UX decisions
- +Works with embedding and import workflows to connect prototypes to research work
- +Configuration supports repeatable study setup across teams
- +Permissioning and workspace separation support controlled access to artifacts
- +Exports and structured outputs make downstream analysis more predictable
- –Automation depends on a limited set of documented integration points
- –Data model complexity can slow schema mapping across multi-study programs
- –Bulk changes across many studies can require manual coordination
- –Role granularity may not match every organization’s RBAC policy
- –Audit and governance visibility can be constrained for external stakeholders
Best for: Fits when product teams need controlled UX studies with consistent artifacts and repeatable configuration across multiple stakeholders.
UserTesting
user research softwareRemote user testing software that coordinates studies, tasks, and recruiting inputs while managing sessions and reporting artifacts.
Study scripting with task-driven sessions that generate shareable findings tied to each participant interaction
UserTesting fits UX research and UI validation teams that need recurring usability sessions tied to product changes. It supports scripted study plans, participant recruitment, and reaction data capture with artifacts that feed design review workflows.
Its value in a UI UX design workflow depends on integration breadth with analytics and ticketing stacks, plus a data model that aligns tasks, sessions, and findings. Admin control and governance hinge on role-based access, workspace configuration, and traceability through activity records.
- +Scripted usability studies tied to specific user tasks and flows
- +Study artifacts map to session-level findings for faster design triage
- +Integration options support connecting findings to design and delivery workflows
- +Role-based access helps separate research authors from reviewers
- –Automation depends on external orchestration since native workflows are limited
- –API coverage can be narrower for fine-grained governance and provisioning
- –Data model granularity varies across artifact types and exports
- –Audit traceability may require careful workspace configuration
Best for: Fits when UX teams run repeatable usability studies and need findings to connect to design and delivery systems.
How to Choose the Right Ui Ux Designing Software
This buyer’s guide covers UI and UX designing software tools for design systems, prototype logic, CMS publishing models, and UX validation workflows. It specifically addresses Figma, Adobe XD, Sketch, Axure RP, Webflow, ProtoPie, InVision, Marvel, Maze, and UserTesting.
The guide turns selection criteria into integration depth, data model fit, automation and API surface, and admin and governance controls. Each section ties those criteria to concrete mechanisms found in the tools, like Figma’s REST API and design system libraries or Webflow’s CMS schema plus API and webhooks.
UI/UX design tooling for prototypes, design systems, and workflow-connected artifacts
UI and UX designing software creates interactive artifacts like component-based designs, responsive artboards, widget-level interaction models, and device-tested prototype flows. These tools help teams reduce drift by using reusable components, variants, and logic layers that carry through review and handoff.
Tooling also needs to plug into downstream workflows through an integration surface. Figma supports API-driven file access and versioned design documents, while Webflow couples a schema-based CMS data model to automation triggers through its API and webhooks.
Mechanisms that determine integration depth, governance, and automation success
Evaluation should focus on how the tool’s data model maps to real workflow objects like components, states, tasks, and findings. Integration depth matters when design artifacts must connect to delivery systems without manual export staging.
Automation and API surface decide whether provisioning, validation, and workflow steps can run through scripts. Admin and governance controls decide whether teams can enforce RBAC, track audit-style events, and contain cross-team access for regulated workflows.
Design-system governed component libraries and variant propagation
Figma propagates component and style updates across files using consistent IDs and update behavior, which supports controlled UI handoff. Sketch’s symbols and symbol overrides provide predictable component reuse and update behavior when teams maintain shared symbol libraries.
Documented API and file access for automation and workflow bridging
Figma exposes a REST API for file reads and workflow automation, which supports API-driven operations on versioned design documents. InVision also supports developer-facing surfaces for automation through API calls and webhooks, which can connect prototype review actions to external pipelines.
Schema-driven data modeling for structured content and automation triggers
Webflow uses CMS collections with explicit field schemas and couples those schemas to automation triggers via its API and webhooks for controlled publishing workflows. This schema alignment reduces ambiguity when teams need deterministic mappings for content updates rather than manual exporting.
Interaction logic layers that compile into testable prototype behavior
Axure RP models conditional interactions and dynamic behaviors per widget, then compiles them into prototype outputs for spec-ready behavior. ProtoPie adds logic variables, conditions, and sensor-driven behaviors so prototypes respond to device input for UX testing on real hardware.
Review traceability anchored to states, tasks, or sessions
InVision links comment threads to specific prototype states and ties feedback to iteration history for review traceability. Maze anchors experience feedback to tasks and user steps inside a UX session, which makes UX decisions traceable to specific steps.
Admin governance coverage with RBAC and audit-style traceability
InVision provides role-based access for controlled review across teams and emphasizes activity and audit-style records for traceability. Figma supports structured collaboration with team-oriented workflows, but advanced governance workflows can require external tooling and process alignment for complex needs.
Pick the tool that matches the required data model and control plane
Start by mapping the required artifact objects to each tool’s underlying data model. Figma is designed around versioned design documents, component variants, and auto-layout logic, while Axure RP centers widget-level interaction configuration compiled to prototype output.
Then validate the automation and control plane. Choose Figma if REST API and component-governed handoff are required, choose Webflow if schema-based CMS publishing must trigger automation via API and webhooks, and choose ProtoPie or Maze when device-connected UX testing or step-level feedback is the primary output.
Match the artifact type to the tool’s core data model
For component-driven UI design where reusable variants must stay consistent across files, Figma and Marvel both store component and variant structures that carry into collaboration workflows. For widget-level interaction specs, Axure RP stores widget behavior configuration and compiles it into prototype artifacts.
Verify the automation and API surface matches workflow throughput needs
If design documents must be accessed and processed by scripts, Figma’s REST API supports file reads and workflow automation on versioned documents. If content provisioning and triggers must be tied to structured CMS schemas, Webflow’s API and webhook-style integrations connect CMS events to automation steps.
Define the expected interaction realism level for validation
If interactive testing must respond to real device inputs like touch and motion, ProtoPie’s logic layer supports variables, conditions, and sensor-driven behaviors for device-tested UX prototypes. If validation depends on step-level observations tied to user tasks, Maze anchors feedback to specific tasks inside a UX session for traceable UX decisions.
Confirm governance controls cover the needed RBAC and audit behavior
If review workflows require role-based access and audit-style traceability, InVision’s role-based access and activity records fit comment-driven prototype review with governance expectations. If governance depends on deep enterprise workflows, Figma and Sketch may require external tooling and process alignment for advanced governance workflows beyond design-time controls.
Check integration depth beyond design exports
Figma’s integration depth includes a plugin ecosystem plus REST APIs for file access and team workflows, which supports custom validators and report generation. Webflow’s integration depth couples API access with webhook triggers tied to CMS events, which reduces manual handoffs when publishing and localization must run through automation.
Which teams get measurable gains from the right UI/UX tool mechanics
Different teams need different control planes for design artifacts. The right choice depends on whether the primary output is a governed design system, a device-tested interaction model, a schema-based publishing pipeline, or step-level research evidence.
The segments below reflect the best-fit match to each tool’s standout mechanisms and stated best-for use cases.
Design system teams needing API-driven handoff with governed component updates
Figma fits this workflow because design system libraries propagate components and styles across files using consistent IDs and update behavior, and the REST API supports automation on versioned documents. Sketch fits teams that prioritize symbol and override propagation with automation through plugins and scripting, but with narrower enterprise governance needs.
Teams prototyping inside Adobe Creative Cloud review loops
Adobe XD fits teams that prototype and hand off inside Creative Cloud workflows because it provides interactive prototypes with triggers and states across responsive artboards plus built-in review comments tied to specific screens. This matches organizations where design assets and review processes remain anchored to Adobe pipelines.
Product teams requiring device-connected UX testing with configurable interaction logic
ProtoPie fits teams that need interactive, device-level UX prototypes because its logic layer supports variables, conditions, and sensor-driven behaviors. This matches teams that must test on real mobile and hardware inputs rather than only scripted animations.
UX research teams running repeatable studies with task-driven evidence
Maze fits product teams that need controlled UX studies because it binds observations to specific tasks inside a UX session and supports repeatable study configuration across stakeholders. UserTesting fits recurring usability sessions because it coordinates study plans, participant recruitment, and task-driven sessions that generate shareable findings tied to each participant interaction.
Marketing and product teams that publish UI-backed experiences from schema models
Webflow fits teams that need schema-based CMS publishing and controlled automation because CMS collections map to explicit field schemas and automation triggers run through the Webflow API and webhooks. This matches workflows where publishing and content updates must be controlled through a deterministic data model.
Failure modes that break automation, governance, or evidence traceability
Many selection failures come from mismatched data model expectations. When the required workflow object does not map cleanly to the tool’s native structure, teams end up rebuilding their own schema mapping around exports.
Other failures come from underestimating governance and audit expectations relative to what the tool’s native controls emphasize.
Assuming an open API exists for enterprise automation when the tool is export-driven
Axure RP automation and extensibility center on Axure project files and export-driven workflows rather than an open API surface, which makes high-throughput automation harder. Figma supports REST API file reads and workflow automation, which fits automation that must operate on versioned design artifacts.
Designing governance processes around RBAC and audit logs that the tool does not emphasize
Adobe XD and Axure RP have limited admin governance, RBAC, and audit-log automation compared with enterprise governance suites, which can require external process alignment. InVision provides role-based access for controlled review and emphasizes activity and audit-style records for traceability, which better supports governed review workflows.
Overcomplicating interaction state without a disciplined logic structure
ProtoPie requires state and data model discipline to avoid tangled interaction logic, which can slow iteration when interaction patterns become highly branched. Maze avoids this specific failure mode by anchoring feedback to tasks and user steps so evidence stays structured even when study setups vary.
Expecting schema-grade relational depth when CMS modeling is simpler
Webflow’s CMS data model depth can be limited for complex relational schemas and joins, which can force workarounds for deeply relational content models. If the primary need is governed UI layout and component consistency rather than relational CMS modeling, Figma’s component variants and auto-layout structures better match the native data model.
Building a cross-tool design system pipeline without planning for normalization overhead
InVision workflows can add cross-tool data model normalization overhead for large design systems, which can break prototype-to-handoff syncing when naming or structure diverge. Figma’s design system libraries propagate updates using consistent IDs, which reduces the need for cross-tool normalization in many component-governed pipelines.
How We Selected and Ranked These Tools
We evaluated Figma, Adobe XD, Sketch, Axure RP, Webflow, ProtoPie, InVision, Marvel, Maze, and UserTesting on features fit, ease of use, and value. Features carried the most weight, because tools that expose the right integration depth, data model structure, and automation surface determine whether teams can keep artifacts governed and connected through the workflow. Ease of use and value each influenced the final placement as a secondary effect when teams needed the mechanism quickly and without extra integration work.
Figma separated itself by combining design system libraries that propagate components and styles across files with consistent IDs and update behavior plus a REST API for file reads and workflow automation on versioned documents. That combination lifted it across both the features factor and the automation success factor, which is why it ranked above tools that lean more on export-driven workflows or narrower API surfaces.
Frequently Asked Questions About Ui Ux Designing Software
Which UI UX designing tools offer API-driven workflows and automation around design artifacts?
How do SSO, RBAC, and audit logging differ across design and UX platforms?
What tools support data migration of design systems or components into a new workflow?
Which products provide admin controls that gate editing, publishing, or collaboration across teams?
Which tools expose extensibility mechanisms that can be configured or provisioned at scale?
What is the practical difference between using Figma vs Adobe XD for responsive prototyping and handoff?
Which tool is best suited for device-level UX prototypes that react to real inputs?
When should teams choose Axure RP over tools like Figma or ProtoPie for interaction modeling?
How do Maze and UserTesting structure UX data so findings map back to specific user actions?
Conclusion
After evaluating 10 art design, 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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