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AI In IndustryTop 9 Best Plate Solving Software of 2026
Ranking roundup of Plate Solving Software for astrophotography, with technical comparisons of ASTAP, AstroPixel Processor, and PixInsight.
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%
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Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
ASTAP
Batch directory solving via configurable CLI parameters and FITS input handling.
Built for fits when automation pipelines need controlled, repeatable plate solving throughput..
AstroPixel Processor
Editor pickSchema-driven plate solving job payloads with API automation and consistent output contracts.
Built for fits when observatory teams need API-driven plate solving with controlled schemas and automation..
PixInsight
Editor pickScripting-driven plate solving that feeds WCS-aware downstream processing in one project.
Built for fits when observatories need local, repeatable solves integrated with image calibration workflows..
Related reading
Comparison Table
The comparison table contrasts plate solving tools by integration depth, including how each project fits into existing imaging pipelines and what API surface supports automation. It also compares the data model and configuration schema, plus admin and governance controls such as RBAC and audit log coverage to evaluate operational fit. Readers can map tradeoffs across throughput, extensibility, and sandboxing patterns for unattended runs.
ASTAP
local solverASTAP runs local plate solving with an indexed star catalog workflow that can be scripted for automated image-to-WCS pipelines.
Batch directory solving via configurable CLI parameters and FITS input handling.
ASTAP targets plate solving workflows by invoking external solving logic from a command-line interface and writing structured results back to the filesystem. The data model centers on FITS inputs plus solver parameters, with output artifacts that downstream automation can parse for coordinates and metadata. Integration depth is driven by configuration files and repeatable CLI invocations, which supports high-throughput batch processing during observing runs.
A key tradeoff is that ASTAP automation is largely integration-by-script rather than a built-in web UI with granular RBAC controls. Astrophotography operators benefit most when they can control catalogs, solver parameters, and logging outputs through provisioning and repeatable command templates. One usage situation is unattended imaging where a scheduler triggers plate solving for every new FITS file and a second process ingests the solved coordinates.
- +Command-line interface enables deterministic batch plate solving
- +Catalog and parameter configuration supports repeatable solves
- +Filesystem outputs integrate with downstream automation parsers
- +Works well with observatory stacks that call external solvers
- –Automation surface is script driven rather than API first
- –Limited native admin controls like RBAC and audit logging
- –Model outputs are file artifacts, not a managed data schema
Observatory automation engineers
Trigger solves for every incoming FITS
Hands-off plate solving workflow
Robotic telescope operators
Re-solve after mount offsets
More consistent pointing solutions
Show 1 more scenario
Astrophotography pipeline builders
Integrate solving into image processing
Automated end-to-end processing
Emits filesystem outputs that feed cropping, alignment, and stacking steps.
Best for: Fits when automation pipelines need controlled, repeatable plate solving throughput.
AstroPixel Processor
desktop plate solvingDesktop plate solving for astrophotography with an integrated workflow for calibration, stacking, and session automation.
Schema-driven plate solving job payloads with API automation and consistent output contracts.
AstroPixel Processor fits teams that already run imaging pipelines and need plate solving integrated into those flows via API calls and automation hooks. Configuration supports repeatable solver parameters and standardized job payloads so outputs stay consistent across nights and operators. The integration approach favors extensibility points for adding steps before and after solving, such as calibration checks or metadata extraction.
A tradeoff is higher setup effort when deployments require strict governance controls and schema alignment across multiple services. AstroPixel Processor works best when plate solving must run at predictable throughput under operator supervision, such as observatory control rooms and scheduled batch runs.
- +API-first job submission for repeatable plate solving runs
- +Configurable solver parameters with standardized job payloads
- +Automation hooks for chaining solving with post-processing steps
- +Data model supports consistent outputs across multiple nights
- –More configuration needed for schema alignment in multi-service setups
- –Governance controls add administrative overhead for small deployments
Observatory operations teams
Run batch plate solving during scheduled sessions
Fewer manual solves
Astrophotography automation developers
Chain solving into calibration and annotation
Automated image triage
Show 2 more scenarios
Science pipeline engineers
Validate outputs against standardized data contracts
More reliable ingest
A structured data model supports consistent fields for downstream consumers.
Platform administrators
Manage access and audit for solving jobs
Clear operational accountability
Governance controls support RBAC-oriented provisioning and audit logging.
Best for: Fits when observatory teams need API-driven plate solving with controlled schemas and automation.
PixInsight
astrophotography suiteAstrophotography platform that includes plate solving and supports scripted automation with a stable project format.
Scripting-driven plate solving that feeds WCS-aware downstream processing in one project.
PixInsight’s plate solving is integrated into its broader workflow graph, so solved WCS and related metadata can feed subsequent calibration, alignment, and measurement steps. The scripting interface enables batch processing across large image sets with repeatable configuration and deterministic execution order. A key integration signal is that plate solving results remain accessible within the same project and processing pipeline rather than exported into a separate system.
A tradeoff is that automation control is focused on PixInsight’s own scripting and processing objects, not a standalone HTTP-style API surface. Batch solving works well when throughput is driven by local workstation or farm orchestration that launches PixInsight projects in controlled sequences. A common usage situation is running the solver after preprocessing frames and then using the same solved coordinate system for stacking, photometry alignment, or mosaics.
- +Solver outputs remain usable inside the same processing pipeline
- +Scripting supports repeatable batch solves across datasets
- +Workflow graph integration reduces WCS export and re-import steps
- +Project-based configuration supports consistent calibration context
- –Automation control is mainly via PixInsight scripts, not external services
- –No native RBAC or audit-log model for multi-admin governance
- –Headless deployment requires running PixInsight in a controlled environment
- –Extensibility favors PixInsight scripting patterns over third-party plug-ins
Astrophotography imaging teams
Batch solve before stacking calibration frames
Higher alignment consistency across nights
Observatory operations staff
Run scripted solves on curated datasets
Fewer manual re-solves per session
Show 2 more scenarios
Workflow engineers
Integrate solving into processing graphs
Reduced WCS handling overhead
The processing graph passes solved coordinates into subsequent tools without external translation.
Research teams
Automate solve-calibrate-measure chains
More reproducible measurement workflows
Solved metadata drives downstream calibration and measurement objects within the same model.
Best for: Fits when observatories need local, repeatable solves integrated with image calibration workflows.
APT (Astro Photography Tool)
imaging automationAcquisition and planning desktop tool with plate solving integration for guiding and imaging control workflows.
WCS-focused solve results that expose field center, scale, and orientation for automated downstream steps.
Astro Photography Tool (APT) centers plate solving by turning captured images into WCS solutions with astrometric calibration. It supports integration with imaging workflows through configurable solve parameters and repeatable solve settings per target and device profile.
The data model focuses on linking solve results to image metadata such as field center, scale, orientation, and confidence outputs. Automation is handled through command-style usage patterns and batch-friendly execution, with an API surface that is mostly file and parameter driven rather than deep service orchestration.
- +Configurable solve parameters per session and target workflow
- +Outputs WCS-centric solution fields for downstream processing
- +Batch-compatible execution patterns for high-volume solves
- –Automation and API surface are limited for server-side orchestration
- –Governance controls like RBAC and audit logs are not first-class
- –Data schema interoperability depends on exported metadata formats
Best for: Fits when imaging pipelines need repeatable plate solving with controlled parameters and WCS outputs.
AllSky Plate Solver
wide-field solvingAll-sky plate solving and astrometry utility integrated into a larger astrophotography toolchain for solving wide fields.
Quality-aware solved-field outputs that can gate automated follow-up actions.
AllSky Plate Solver performs plate solving by matching sky images to indexed star fields to return pointing solutions. Integration focuses on automation around image input, solver configuration, and result consumption for observatory workflows.
The data model centers on astrometric outputs such as solved coordinates and quality indicators that can feed downstream framing, pointing, and logging systems. Extensibility depends on how easily external orchestration can supply frames and retrieve results through supported interfaces.
- +Produces standard astrometric outputs for downstream pointing workflows
- +Solver configuration supports deterministic behavior across repeated runs
- +Integration can be driven by scripted pipelines and observatory automation
- +Result quality fields support automated acceptance thresholds
- –Limited visibility into administrative controls for multi-operator environments
- –Automation depends on external orchestration for queueing and retries
- –Audit trail and RBAC details are not clearly exposed through a defined schema
- –API surface documentation may be insufficient for high-throughput governance
Best for: Fits when observatory operators need controlled plate-solving integration into existing automation pipelines.
AstroTortilla
server plate solvingLocal plate solving server that exposes HTTP-based automation for integration into imaging and capture pipelines.
Headless command-line plate solving that writes WCS results from FITS images.
AstroTortilla is a plate solving tool that focuses on fast astrometric matching for astronomical images. It uses a local workflow model that runs solver logic and produces WCS outputs from image inputs.
Integration depth is centered on command-line execution and filesystem-based input and output, with limited native automation hooks. The data model is primarily FITS-centric, with configuration files driving solver parameters and output artifacts.
- +Command-line execution supports scripted, headless plate solving workflows
- +FITS input and WCS output map directly onto common astronomy pipelines
- +Configuration-driven runs support repeatable solver settings per dataset
- +Local execution reduces reliance on external services for solving
- –Limited documented API surface restricts fine-grained automation control
- –Provisioning and RBAC controls are not part of the core workflow
- –Audit logging and governance features are not exposed as first-class outputs
- –Extensibility is mostly config and wrapper-based rather than schema-driven
Best for: Fits when solo operators or small pipelines need scripted, repeatable plate solving without an API.
Siril Plate Solver (forked utilities excluded)
self-hosted utilitiesCommunity-maintained plate solving utilities hosted on GitHub that can be embedded into automation scripts for local solving.
In-process Siril workflow integration that writes astrometric results back into the running session.
Siril Plate Solver (forked utilities excluded) concentrates on plate solving within Siril, using the existing image-processing pipeline rather than introducing a separate service layer. It integrates tightly with Siril workflows for generating solutions from calibrated inputs and writing results back into the session context.
Automation is mainly driven through Siril’s scripting hooks and command-style usage, not a standalone HTTP API. The data model centers on solver inputs, astrometric results, and session state, which limits external governance and RBAC capabilities.
- +Tight integration with Siril image pipeline and session context
- +Works with calibrated inputs produced in the same workflow
- +Script-driven runs through Siril automation hooks
- +Clear input-output flow for plate solving targets and results
- –No documented REST API surface for external orchestration
- –Limited schema for external data modeling beyond Siril session context
- –Automation is constrained to Siril scripting rather than agent APIs
- –No RBAC, audit log, or admin governance controls described
Best for: Fits when observatory workflows already run inside Siril and need scripted plate solves.
CCDOps Plate Solver
imaging suiteAstrophotography imaging software with built-in plate solving support for telescope alignment workflows.
External invocation model that returns astrometric results for batch or scripted workflows.
CCDOps Plate Solver is a plate solving tool from CCD Astronomy that targets integration with existing CCD imaging pipelines. It focuses on submitting image data to an external solve process and returning astrometric results usable for downstream automation.
The interface centers on configuration choices that affect solve accuracy and tolerance settings. Automation integration depth depends on how well the tool’s invocation and output format fit the caller’s workflow and data model.
- +Image-to-solution workflow fits scripted CCD processing pipelines
- +Configurable solve parameters support repeatable astrometric outcomes
- +Output results can be consumed by downstream automation steps
- +Lightweight usage pattern suits high-throughput batch solving
- –API and schema surface for automation is limited in published documentation
- –No clear RBAC model or multi-tenant governance controls are described
- –Audit logging and provenance details are not clearly documented
- –Extensibility via custom adapters is not specified in available materials
Best for: Fits when imaging operators need batch astrometry that plugs into existing scripts and jobs.
Ekos (plate solving plugins excluded)
imaging controlImaging control software in the KStars Ekos family with plate solving capabilities through modular solver components.
Imaging sequence orchestration that coordinates capture, focusing, and guiding phases.
Ekos (plate solving plugins excluded) runs image capture, framing, focus, guiding, and sequencing into a connected imaging workflow inside a KDE-focused toolchain. It offers a structured data model for device roles like mount, camera, focuser, and guider, with state transitions that keep dependent steps in sync.
Automation comes through scheduling and scripted sequences with configuration that can be exported and reused across sessions. The main integration depth is controlled through its plugin-style component architecture and predictable configuration points for throughput-critical observing runs.
- +Deep device-role integration with mount, camera, focuser, and guider state coordination
- +Sequencing supports multi-step automation across capture, focus, and guide phases
- +Configuration and workflow states are reusable across observing sessions
- +Extensible component model enables additional hardware support paths
- +KDE integration aligns UX behavior with other KDE applications
- –Automation control is concentrated in UI-driven flows instead of a first-class automation API
- –Integration depends on installed components and matching hardware drivers
- –Extensibility is practical but lacks a clearly documented external schema boundary
- –Higher concurrency limits can appear during heavy imaging and calibration steps
- –Fine-grained governance controls for multi-user operations are not a primary focus
Best for: Fits when observatories need repeatable imaging workflows with tight device state coordination.
How to Choose the Right Plate Solving Software
This buyer's guide covers nine plate solving tools used in astrophotography workflows, including ASTAP, AstroPixel Processor, PixInsight, APT, AllSky Plate Solver, AstroTortilla, Siril Plate Solver, CCDOps Plate Solver, and Ekos. It focuses on integration depth, data model behavior, automation and API surface, and admin governance controls that affect how plate solving fits into an imaging pipeline.
The guide maps concrete mechanisms like schema-driven job payloads in AstroPixel Processor and batch directory solving in ASTAP to selection decisions that teams make when throughput and repeatability matter. It also flags governance gaps like the lack of native RBAC and audit logging in ASTAP, PixInsight, APT, AllSky Plate Solver, and AstroTortilla.
Plate solving that turns telescope images into WCS coordinates via an automation-ready workflow
Plate solving software matches star fields in captured images to an indexed catalog and returns an astrometric solution in WCS form, plus quality or confidence fields that can gate downstream steps. The main operational goal is converting image inputs into repeatable, machine-consumable outputs that imaging systems can ingest without manual reconfiguration.
Tools like ASTAP run local command-line solving that writes filesystem artifacts for downstream parsers, while AstroPixel Processor uses schema-driven plate solving job payloads that standardize inputs and outputs for API automation. PixInsight keeps plate solving inside a node-based processing pipeline so the WCS context can remain usable inside the same project.
Evaluation criteria that determine automation control and integration fit
Plate solving tool choice hinges on how outputs and configuration move between capture, solving, and post-processing systems. Integration depth matters most when solving must feed guiding, framing, or calibration steps with minimal translation.
The next differentiator is the data model, because file-based artifacts and unmanaged formats increase glue code while schema-driven job payloads reduce mapping work. Automation and API surface matter when multiple operators or services need consistent throughput, especially when RBAC, audit logs, and governance are required.
API-first job submission with schema-driven input-output contracts
AstroPixel Processor provides schema-driven plate solving job payloads for repeatable runs, with standardized job payloads that reduce mapping drift across nights. This same schema behavior helps when orchestration systems need predictable throughput and consistent output contracts.
Deterministic batch directory solving with configurable CLI parameters
ASTAP supports batch directory solving via configurable CLI parameters and FITS input handling, which helps imaging teams run controlled image-to-WCS pipelines. AstroTortilla also supports headless command-line solving that writes WCS results from FITS images, but it lacks a documented API surface for fine-grained automation.
Integration that keeps WCS usable inside the same processing project
PixInsight keeps plate solving inside a node-based workflow and uses scripting hooks to enable repeatable solves across datasets. This approach reduces WCS export and re-import steps compared with tools that output file artifacts for external workflows.
WCS-centric solve outputs for field center, scale, orientation, and confidence gating
APT exposes WCS-focused fields that include field center, scale, orientation, and confidence outputs for downstream automation. AllSky Plate Solver adds quality-aware solved-field outputs that can gate automated follow-up actions based on quality indicators.
In-process plate solving tied to a session context state machine
Siril Plate Solver integrates tightly with Siril workflows by generating solutions from calibrated inputs and writing results back into the running session context. Ekos coordinates capture, focusing, and guiding with sequencing and device-role state coordination, so solved context can remain aligned with imaging steps.
Admin governance controls that support multi-operator operational safety
Some tools provide limited governance primitives, and that affects multi-user operations even when solving is reliable. ASTAP, PixInsight, APT, AllSky Plate Solver, and AstroTortilla all show limited native admin controls such as RBAC and audit logging, so governance is often handled outside the tool in wrappers.
A decision framework for plate solving integration, automation, and governance
Start by mapping how plate solving results must flow into capture, guiding, calibration, and post-processing so integration depth matches the pipeline. Then choose tools based on whether automation needs schema-driven API contracts, filesystem-based batch artifacts, or in-project scripting.
Finally, confirm governance requirements by checking whether RBAC and audit logging exist as first-class outputs, because several tools emphasize local execution and scripting rather than managed multi-admin control.
Pick an automation surface that matches the orchestration model
If the pipeline calls services via structured payloads, choose AstroPixel Processor because it supports API automation with schema-driven job payloads and consistent output contracts. If the pipeline expects deterministic local execution, choose ASTAP for batch directory solving through a configurable CLI and FITS input handling.
Choose the data model that minimizes translation glue code
If standardization across services matters, prefer AstroPixel Processor because schema-based inputs and consistent outputs support multi-night repeatability. If the pipeline is already organized around a single processing environment, choose PixInsight because plate solving stays inside the same node-based project and remains WCS-aware for downstream nodes.
Align output fields to downstream acceptance and gating logic
For automation that needs explicit field center, scale, orientation, and confidence, choose APT because it exposes WCS-centric solution fields and confidence outputs. For pipelines that require quality-aware gating of follow-up actions, choose AllSky Plate Solver because it returns quality indicators alongside solved astrometric outputs.
Match execution context to where imaging states live
If plate solving must write results into an active session workflow, choose Siril Plate Solver because it runs in Siril and writes astrometric results back into the session context. If plate solving must align with device-role state coordination across mount, camera, focuser, and guider, choose Ekos because sequencing and state transitions keep dependent steps in sync.
Validate governance needs before committing to local scripting-only tools
If multi-admin governance needs RBAC and audit logging as managed features, plan for tools like AstroPixel Processor to fit better than tools with limited native controls. If governance features are not first-class in the tool, wrappers and external orchestration must provide RBAC and audit logs, which is the reality for ASTAP, PixInsight, APT, AllSky Plate Solver, and AstroTortilla.
Lock the integration boundary around stable file formats or schema contracts
If the integration boundary is filesystem artifacts, choose ASTAP or AstroTortilla because both produce WCS outputs that downstream automation can parse from local runs. If the integration boundary is message-like job payloads, choose AstroPixel Processor because its schema-driven job payloads reduce format drift between orchestrators.
Which teams benefit from different plate solving integration models
Different plate solving tools target different automation control patterns, which changes the best fit for imaging operations. The strongest matches follow from how each tool handles integration depth, output structure, and orchestration control.
The segments below map to the actual best-fit scenarios for ASTAP, AstroPixel Processor, PixInsight, APT, AllSky Plate Solver, AstroTortilla, Siril Plate Solver, CCDOps Plate Solver, and Ekos.
Observatory teams that need API-driven plate solving with controlled schemas
AstroPixel Processor fits teams that want API automation with schema-driven plate solving job payloads and consistent output contracts. This approach reduces schema alignment work across multiple services compared with tools that rely on script-driven parameters.
Operations teams running controlled local throughput pipelines that call an external solver
ASTAP fits workflows that need deterministic batch directory solving with configurable CLI parameters and FITS input handling. This choice matches pipelines that want repeatable image-to-WCS outputs as filesystem artifacts for downstream automation parsers.
Studios and observatories that keep plate solving inside a single image-processing project
PixInsight fits environments that want node-based workflow integration where solver outputs remain usable inside the same processing pipeline. Its scripting hooks support repeatable batch solves across datasets without external orchestration as the primary integration boundary.
Imaging operators that need WCS fields for guiding and automated framing decisions
APT fits operators who need solve results that expose field center, scale, orientation, and confidence outputs for automated downstream steps. AllSky Plate Solver fits teams that need quality-aware solved-field outputs that gate follow-up actions.
Teams that already run inside Siril or Ekos and want tight session or device state coordination
Siril Plate Solver fits observatory workflows that already run inside Siril and require scripted plate solves tied to calibrated inputs and session context. Ekos fits observatories that need repeatable imaging workflows with tight device-role state coordination across capture, focusing, and guiding phases.
Practical pitfalls that break integrations and governance expectations
Plate solving tools often work correctly in isolation but fail during orchestration because integration boundaries and output structures do not match the pipeline. Governance gaps also appear when multiple operators need RBAC and audit trails built into the solving layer.
The mistakes below reflect concrete cons such as limited API surfaces, file-artifact output models, and governance controls that are not first-class in tools like ASTAP, APT, PixInsight, AstroTortilla, and AllSky Plate Solver.
Assuming local CLI output behaves like a managed data schema
ASTAP produces model outputs as file artifacts rather than a managed data schema, which increases parsing and mapping work in multi-service pipelines. AstroTortilla also writes WCS results from FITS images and limits automation control through a mostly documented command-line interface, so schema expectations must be handled in orchestration.
Treating scripting-only automation as an API for multi-service orchestration
PixInsight automation is driven mainly through PixInsight scripting hooks rather than external services, so other services cannot rely on a stable external API boundary. Siril Plate Solver and APT also lean on command-style or scripting-driven automation, so cross-service orchestration should be designed around their execution context.
Overlooking RBAC and audit logging needs until deployment time
ASTAP has limited native admin controls such as RBAC and audit logging, and PixInsight plus APT show no native RBAC or audit-log model for multi-admin governance. AllSky Plate Solver and AstroTortilla also do not expose audit trail and RBAC details through a defined schema, so governance must be implemented outside the solver layer.
Ignoring quality fields that are required for automated acceptance gates
If pipelines need automated acceptance thresholds, APT and AllSky Plate Solver provide confidence or quality indicator outputs that can gate follow-up actions. Tools that only return solved coordinates without clear quality semantics can force extra heuristics in wrappers.
Building queueing and retry logic into the solver instead of orchestration
AllSky Plate Solver describes automation that depends on external orchestration for queueing and retries, which means the retry policy belongs in the orchestrator. CCDOps Plate Solver similarly uses an external invocation model, so throughput controls like retries and backoff must be handled in the caller workflow rather than inside the solver.
How We Selected and Ranked These Tools
We evaluated ASTAP, AstroPixel Processor, PixInsight, APT, AllSky Plate Solver, AstroTortilla, Siril Plate Solver, CCDOps Plate Solver, and Ekos using feature fit for plate solving automation, ease of integration and usability, and value for repeatable WCS workflows. Each tool receives an overall score built from features at the largest share, while ease of use and value each contribute the same smaller share. This ranking reflects criteria-based scoring of the mechanisms shown in the tool capabilities and constraints, including whether the automation surface is API-first, schema-driven, or script and filesystem driven.
ASTAP set itself apart from lower-ranked options through deterministic batch directory solving via configurable CLI parameters and FITS input handling, which lifted it most on the features factor because it directly supports controlled, repeatable throughput in automation pipelines.
Frequently Asked Questions About Plate Solving Software
How does API-driven automation differ between AstroPixel Processor and command-line tools like ASTAP?
Which tools keep plate solving inside an image-processing workflow instead of calling an external solver?
What integration path fits observatories that already run Ekos device orchestration?
How do the tools represent solve results and quality signals for automated follow-up?
Which plate solvers are most suitable for headless batch runs across many FITS images?
What common setup issues cause plate solves to fail, and how can the tool choice reduce friction?
How do data migration and configuration reuse typically work when moving an automation pipeline between tools?
What security and admin governance options exist when multiple operators share a solve system?
How do extensibility mechanisms differ across PixInsight scripting and external-orchestrator approaches like CCDOps Plate Solver and ASTAP?
Conclusion
After evaluating 9 ai in industry, ASTAP 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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