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Technology Digital MediaTop 10 Best Cpu Gpu Monitoring Software of 2026
Top 10 cpu gpu monitoring software roundup for PCs and servers, with AIDA64, HWMonitor, HWiNFO, MSI Afterburner features, tradeoffs, and ranking.
How we ranked these tools
An editor sets the topic, the inclusion criteria, and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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If you want quick single-host GPU monitoring with repeatable logs and an overlay, MSI Afterburner is the best pick, whereas HWMonitor fits when you need fast CPU and GPU sensor visibility for manual thermal or workload checks.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
MSI Afterburner
GPU fan curve editing and clock control integrated with live sensor overlays.
Best for: Fits when single-host GPU monitoring and tuning need fast overlays and repeatable logs.
HWMonitor
Editor pickDirect hardware sensor readout across many components, presented as raw telemetry rather than summarized performance counters.
Best for: Fits when a single host needs quick sensor visibility for manual thermal or workload checks.
HWiNFO
Editor pickPer-sensor telemetry collection with fine-grained polling and time-series logging in one host tool.
Best for: Fits when lab teams need detailed host telemetry captures across CPU and GPU sensors.
Comparison Table
MSI Afterburner
gamingMSI Afterburner monitors GPU metrics and provides overclocking controls with an on-screen overlay.
GPU fan curve editing and clock control integrated with live sensor overlays.
MSI Afterburner is a host-based monitoring tool that focuses on local sensor polling, real-time overlay rendering, and configurable logging. The dashboard supports multiple display modes so GPU and CPU temperature, utilization, and clock telemetry can be reviewed during normal use or benchmark sessions. Its control surface includes GPU overclocking and fan curve editing, which keeps monitoring and tuning in one workflow.
A key tradeoff is that Afterburner’s monitoring depth is strongest for sensors exposed to the Windows driver stack, so some CPU package-level details or less common sensor endpoints may be absent. It fits best on a single workstation where a user wants quick GPU overlay visibility during gaming and also wants repeatable logs during stability testing.
- +Real-time on-screen overlay with configurable layout for GPU tuning sessions
- +Tight pairing of monitoring and GPU clock, voltage, and fan curve control
- +Historical charting and log export for reviewing thermal and performance trends
- +Per-application overlay helps validate workload behavior without leaving the game
- –Sensor coverage depends on what GPU and CPU drivers expose on Windows
- –Logging setup and overlay tuning take manual configuration to match the workflow
PC enthusiasts
Validate overclocks during gaming
Fewer unstable tuning sessions
Benchmarking analysts
Compare runs using exported logs
Clear run-to-run differences
Show 2 more scenarios
QA and performance testers
Monitor app load in overlay mode
Faster repro of bottlenecks
Run per-app overlays to see whether CPU load and GPU utilization match test scripts.
Overclocking technicians
Stabilize systems under sustained load
More reliable stability checks
Use historical charts to catch thermal throttling indicators and verify stable clock behavior.
Best for: Fits when single-host GPU monitoring and tuning need fast overlays and repeatable logs.
HWMonitor
desktopHWMonitor displays CPU and GPU temperatures, voltages, fan speeds, clocks, and utilization.
Direct hardware sensor readout across many components, presented as raw telemetry rather than summarized performance counters.
HWMonitor targets PC and workstation troubleshooting where quick visibility into hardware telemetry matters more than building an instrumentation pipeline. It reads hardware sensor data and shows it in a compact UI for CPU temperature, fan behavior, and power-related values tied to available device sensors. GPU visibility is present when the system exposes compatible sensor interfaces, which is common on many desktop setups but not universal across every GPU vendor stack.
The tradeoff is limited integration depth, since HWMonitor does not provide a published agent or API surface for programmatic metrics ingestion. It fits situations like lab PC bring-up, driver validation, or manual thermal investigation where a single host can be monitored while workload changes. It also works when historical review matters, since exported logs can be analyzed outside the app.
- +Fast live view of hardware sensor telemetry with low configuration
- +Exports monitoring data for later review without dashboard tooling
- +Shows many raw device sensor readings beyond common OS counters
- +Lightweight footprint makes it practical during troubleshooting
- –No documented API or automation hooks for external monitoring systems
- –GPU sensor coverage depends on what the host exposes to it
- –No per-process GPU attribution for workload-level GPU attribution
- –Polling-based sampling can miss short thermal spikes
PC support technicians
Diagnose overheating after a workload change
Pinpoints thermal runaway triggers
Overclocking hobbyists
Validate stability of CPU settings
Reduces unstable configuration iterations
Show 2 more scenarios
Lab engineers
Log hardware telemetry during tests
Improves repeatability of experiments
Export time-stamped readings from a test PC to compare configurations offline.
GPU QA testers
Check GPU temperature and clock behavior
Detects thermal throttling patterns
Monitor GPU-related sensor values while running repeatable validation workloads.
Best for: Fits when a single host needs quick sensor visibility for manual thermal or workload checks.
HWiNFO
desktopHWiNFO reports detailed CPU, GPU, memory, storage, voltage, temperature, and fan data.
Per-sensor telemetry collection with fine-grained polling and time-series logging in one host tool.
HWiNFO reads hardware sensor telemetry using its built-in sensor engines, so monitoring can include CPU temperature, fan speed, power draw, and clocks alongside utilization metrics. It offers historical logging and export so teams can review spikes after a test run. GPU coverage includes multiple sensor domains and utilization views when the driver exposes telemetry.
A key tradeoff is that sensor availability depends on the hardware, BIOS settings, and GPU driver exposure, so some sensors may be missing or renamed across systems. A strong usage fit is local troubleshooting and bench testing where one operator needs fast visibility and can tune the polling interval and logging scope for a short test window.
- +Very broad hardware sensor coverage with per-component telemetry views
- +Configurable polling interval and logging scope for controlled test captures
- +Detailed GPU and CPU sensor pages that match driver-exposed metrics
- +Exportable historical logs for post-run troubleshooting
- –Sensor availability varies by hardware and GPU driver exposure
- –Configuration screens and data filtering can be complex during first setup
- –Automation and integration require extra scripting rather than built-in API workflows
- –Large sensor sets can overwhelm dashboards during live sessions
IT staff in labs
Bench-test thermal and power behavior
Repeatable thermal test evidence
Performance engineers
Correlate utilization with workload spikes
Faster root-cause narrowing
Show 2 more scenarios
Gamers and enthusiasts
Validate GPU clocks under load
Less thermal throttling surprises
Monitor GPU sensor readings during gameplay to confirm stable frequencies and thermal limits.
Server administrators
Diagnose hardware sensor anomalies
Quicker remediation actions
Review sensor logs for overheating and fan control irregularities on monitored hosts.
Best for: Fits when lab teams need detailed host telemetry captures across CPU and GPU sensors.
NZXT CAM
gamingNZXT CAM monitors CPU and GPU temperatures, utilization, clocks, and system performance.
CAM’s tight NZXT device integration drives unified fan and lighting control next to live CPU and GPU telemetry.
NZXT CAM couples CPU and GPU telemetry with an overlay and hardware-centric dashboards for systems that match NZXT’s device ecosystem. It provides real-time sensor charts for utilization, temperatures, clocks, power draw, and fan behavior while also tracking per-app activity in the CAM UI.
- +In-app sensor dashboards show CPU and GPU utilization alongside temps and power draw
- +Fast overlay workflow helps verify performance during games
- +Integrates fan control and RGB behavior when NZXT hardware is present
- +Per-application views make it easier to correlate activity with resource spikes
- –Limited automation and API access constrains programmatic collection pipelines
- –Remote monitoring and host-to-host fleet management are not CAM’s primary focus
- –Sensor coverage can vary by GPU model and driver support
- –Advanced alerting and log export for long retention require external workarounds
Best for: Fits when PC builders need local CPU and GPU monitoring with overlay and device control.
Netdata
enterpriseNetdata collects real-time CPU, GPU, memory, disk, network, and application metrics.
Built-in time-series graphing driven directly by its streaming collectors and alert conditions.
Netdata collects CPU and GPU sensor telemetry from host systems and streams it into real-time dashboards with historical time-series retention. It pairs an agent-first deployment with a telemetry ingestion pipeline that can export data to other tools and drive alerting on threshold breaches.
- +Real-time host dashboards with historical time-series retention built in
- +Agent-based collection supports many machines with consistent metric naming
- +Alerting can trigger on threshold conditions over streamed metrics
- +Data export options fit integrations that need time-series outside Netdata
- –GPU coverage depends on installed GPU telemetry sources and collectors
- –High-cardinality environments can stress ingestion and storage throughput
Best for: Fits when teams need continuous CPU and GPU telemetry across many hosts with exportable time-series history.
Open Hardware Monitor
open-sourceOpen Hardware Monitor reads CPU, GPU, motherboard, storage, fan, clock, and load sensors.
Selectable sensor logging tied to the same live telemetry view, with polling interval control for consistent time-series captures.
Open Hardware Monitor is a host-based hardware sensor reader that can display CPU and GPU telemetry from common monitoring-capable drivers. It provides a real-time sensor list with clocks, temps, fan speeds, power draw, and utilization readings, then exports values through selectable output logging.
- +Direct sensor telemetry view with temperatures, clocks, power, and fan speed
- +Configurable polling interval to control update cadence and reduce sensor churn
- +Local logging output supports exporting time-series sensor values
- +Works as a lightweight host tool for systems without a monitoring agent
- –Limited automation surface compared with tooling that exposes APIs for polling
- –GPU coverage depends on the device driver and available sensor providers
- –No built-in per-process attribution for GPU work like per-application telemetry
- –Remote monitoring requires external plumbing rather than a built-in network UI
Best for: Fits when a PC workstation or small lab needs local CPU and GPU sensor logging without a centralized server.
MangoHud
gamingMangoHud overlays CPU and GPU utilization, temperatures, clocks, frame rates, and frame times.
Application-window overlay for per-process telemetry using a lightweight runtime hook and configurable on-screen layout.
MangoHud overlays per-process performance telemetry on top of an application window, which makes it different from toolsets that rely on separate dashboards. It reads hardware sensor telemetry and performance counters and can show CPU and GPU utilization, clocks, temperatures, and power draw in real time.
- +In-window overlay makes GPU and CPU utilization readable during gameplay or tuning
- +Per-process focus supports attribution when benchmarking multiple workloads back-to-back
- +Text configuration plus environment variables supports repeatable launch setups
- +Logging output enables later review of thermal throttling patterns and clock changes
- –No native web dashboard or remote monitoring for cross-host visibility
- –Sensor coverage varies by platform and driver stack, which can leave fields blank
- –Per-process attribution is limited by how the target process maps onto GPU usage
- –High sampling rates increase overhead and can affect latency-sensitive tests
Best for: Fits when local GPU and CPU telemetry must be visible during runs and later inspected from logs.
AIDA64
desktopAIDA64 combines hardware diagnostics, sensor monitoring, stress testing, and reporting.
Sensor history logging that ties telemetry over time to a stable hardware inventory layout.
AIDA64 turns hardware sensor telemetry into a long-running monitoring view geared for PC and workstation troubleshooting. Core monitoring covers CPU and GPU utilization, temperatures, fan speeds, clock frequency, and power draw, with a choice of polling intervals for telemetry refresh.
- +Broad sensor coverage across CPU, GPU, thermals, clocks, and power draw
- +Historical time-series logging supports post-incident review
- +Polling interval control helps balance freshness and measurement overhead
- +Hardware inventory and monitoring share a consistent hardware mapping
- –Per-process CPU and GPU attribution is not the primary monitoring focus
- –Remote monitoring needs a separate setup path rather than a single agent install
- –Alerting and notification workflows are lighter than dedicated monitoring platforms
- –UI density increases the time needed to find a specific metric quickly
Best for: Fits when desktop and workstation debugging needs sensor history without building a full monitoring stack.
AMD Software: Adrenalin Edition
vertical specialistAMD Software: Adrenalin Edition provides Radeon GPU metrics, performance overlays, recording, and tuning.
In-game overlay that ties AMD driver metrics to the currently running application without separate tooling.
AMD Software: Adrenalin Edition reads CPU and GPU telemetry for AMD graphics and surfaces it in overlay and dashboard views for real-time monitoring. It provides per-app performance metrics, including utilization and frame-related stats where supported, using GPU driver instrumentation rather than a generic sensor reader.
- +Driver-integrated telemetry for AMD GPUs with low-latency on-screen overlays
- +Per-application GPU stats help correlate spikes with running software
- +Built-in fan and tuning controls reduce context switching during tuning
- +Telemetry refresh is consistent with interactive GPU workload changes
- –Monitoring depth depends heavily on AMD hardware and driver support
- –Export and automation capabilities are limited versus tools with external APIs
- –CPU-only sensor parity is weaker than PC-focused monitoring specialists
- –Remote monitoring and host fleet governance are not a native workflow
Best for: Fits when AMD GPU owners need quick on-screen telemetry and per-app correlation during tuning or gaming.
NVIDIA App
vertical specialistNVIDIA App provides GeForce performance overlays with GPU utilization, temperatures, clocks, and frame rates.
Per-process GPU attribution inside NVIDIA App’s NVIDIA driver telemetry view
NVIDIA App targets systems with NVIDIA GPUs and focuses monitoring on the driver stack, not generic hardware telemetry. It surfaces GPU utilization, temperatures, clocks, and power data, and it can attribute activity to processes visible in the NVIDIA driver context.
- +Driver-context GPU metrics update without separate sensor databases
- +Process-level GPU attribution shows which processes drive GPU activity
- +Works well on NVIDIA GPU systems where vendor telemetry is reliable
- +Low-friction UI for temperatures, clocks, and power draw
- –CPU sensor coverage is thin versus host monitoring tools
- –Remote monitoring and alert automation are limited to NVIDIA ecosystem workflows
- –Historical time-series export is not a primary monitoring workflow
- –Feature set depends on NVIDIA driver and supported GPU families
Best for: Fits when teams need NVIDIA-focused monitoring tied to the driver for workstation and GPU troubleshooting.
Conclusion
After evaluating 10 cpu gpu monitoring software, MSI Afterburner 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.
How to Choose the Right Cpu Gpu Monitoring Software
CPU and GPU monitoring software covers on-host telemetry viewing, time-series logging, and per-process attribution so teams can connect CPU load, thermals, and GPU utilization to the workloads that drive them. This guide covers ten tools across Windows-first utilities, host telemetry loggers, and device-integrated overlays, including MSI Afterburner, HWiNFO, and AIDA64.
The standout workflow differences show up in how each tool collects sensor telemetry, how it records history for post-incident review, and how far automation and external integrations can go. MSI Afterburner pairs live overlays with direct GPU fan curve and clock control, while HWiNFO focuses on per-sensor polling and structured logging.
CPU and GPU monitoring software for PC and server telemetry, logging, and per-process attribution
CPU and GPU monitoring software reads hardware sensor telemetry such as utilization, temperatures, power draw, clocks, and fan speed and turns it into live dashboards and historical time-series logs. Tools like HWiNFO provide per-sensor telemetry views with configurable polling intervals and logging scope for controlled test captures across CPU and GPU sensors.
AIDA64 emphasizes sensor history logging tied to a stable hardware inventory layout, which supports post-incident review without building a separate monitoring stack. By contrast, MSI Afterburner combines live GPU sensor overlays with repeatable GPU tuning controls, which changes the monitoring role from passive observation to an interactive feedback loop during GPU clock, voltage, and fan curve adjustments.
CPU and GPU monitoring feature checklist for telemetry, logging, and attribution
CPU and GPU monitoring tools turn hardware sensor telemetry into usable signals for troubleshooting and capacity planning. Teams need live overlays for fast feedback and time-series logging for post-incident review.
The largest differences across this category show up in how tools poll sensors, how they record history, and how they connect metrics back to workloads. MSI Afterburner combines live GPU overlays with direct GPU clock, voltage, and fan curve control, while HWiNFO emphasizes per-sensor polling and structured time-series logging.
Live sensor overlays tied to GPU tuning or driver context
MSI Afterburner provides real-time on-screen overlays configured for GPU tuning sessions alongside GPU clock, voltage, and fan curve control. NZXT CAM also shows CPU and GPU utilization, temperatures, and power draw in a local overlay, while NVIDIA App and AMD Software: Adrenalin Edition focus on driver-integrated, per-application telemetry views.
Per-sensor telemetry collection with controllable polling and logging scope
HWiNFO collects per-sensor telemetry with configurable polling interval and logging scope for controlled test captures. Open Hardware Monitor adds selectable sensor logging tied to its live telemetry view with polling interval control, while HWMonitor focuses on fast raw sensor readouts with low configuration and exports for later review.
Historical sensor history for post-incident review
AIDA64 emphasizes sensor history logging tied to a stable hardware inventory layout for consistent post-incident comparison. Netdata provides built-in time-series graphing driven by its streaming collectors and alert conditions, and it retains historical telemetry as part of its continuous monitoring approach.
Workload correlation and per-process attribution
NVIDIA App includes process-level GPU attribution inside its NVIDIA driver telemetry view, which helps link GPU activity to specific running processes. MangoHud overlays per-process telemetry for focused inspection during runs, while MSI Afterburner improves workload feedback by pairing monitoring with repeatable GPU control during tuning sessions.
Fleet-style continuity versus single-host instrumentation
Netdata supports agent-based collection across many machines with consistent metric naming and historical time-series retention. HWiNFO, HWMonitor, and Open Hardware Monitor primarily operate as single-host telemetry tools where history capture is configured on the host.
How to choose CPU GPU Monitoring Software by workflow and control depth
A CPU and GPU monitoring stack choice should start with the workflow shape: local tuning, lab telemetry capture, or continuous multi-host monitoring with retention. The tool selection changes when monitoring must drive actions through clock and fan control, or when alerts must be generated from streaming collectors.
Next, the decision should map to collection mechanics. HWiNFO and Open Hardware Monitor trade setup complexity for per-sensor detail and controlled capture, while Netdata trades sensor breadth for continuous time-series streaming and retention across hosts.
Pick the primary usage loop: tuning feedback or measurement capture
Choose MSI Afterburner when the workflow needs live GPU overlays while adjusting GPU clock, voltage, and fan curve for repeatable tuning sessions. Choose HWiNFO when the workflow needs per-sensor telemetry collection with configurable polling interval and logging scope for controlled test captures.
Decide between single-host telemetry tools and continuous multi-host monitoring
Choose Netdata when continuous host dashboards, historical time-series retention, and streaming alert conditions are the core requirement. Choose HWMonitor, Open Hardware Monitor, or HWiNFO when the goal is local sensor visibility and captured logs from one workstation or lab host.
Match external integration needs to the tool’s automation surface
If external monitoring systems and automation hooks are required, prioritize tools that support export workflows and avoid relying on tools that provide no documented API. HWMonitor and CAM both limit programmatic collection pipelines, while Netdata’s streaming collectors and alert conditions support ongoing integration patterns.
Select based on sensor detail depth versus operational simplicity
Choose HWiNFO when sensor availability varies and the tool must still provide fine-grained per-sensor polling and time-series logging within the same host tool. Choose HWMonitor when the priority is quick sensor visibility with low configuration using direct hardware sensor readouts.
Validate workload attribution requirements against the process model
Choose NVIDIA App when process-level GPU attribution inside NVIDIA driver telemetry is required for workstation or GPU troubleshooting. Choose MangoHud when per-process GPU and CPU telemetry must be visible in an application-window overlay during runs.
Confirm device scope by GPU vendor and driver integration points
Choose AMD Software: Adrenalin Edition or NVIDIA App when driver-integrated telemetry and per-application correlation on AMD or NVIDIA hardware are the main target. Choose MSI Afterburner, HWiNFO, or AIDA64 when the requirement is broader sensor coverage across CPU, GPU thermals, clocks, and power draw.
Who should use CPU GPU Monitoring Software for PC and server telemetry
The right tool depends on whether telemetry is used for interactive tuning, lab-grade captures, or ongoing visibility across many hosts. The category also splits by whether per-process GPU attribution drives the troubleshooting workflow or whether host-level sensor history is sufficient.
This guide’s tools cover Windows-first utilities, host telemetry loggers, and device-integrated overlays, which maps to common PC and server operations like performance verification and thermal stability checks.
GPU tuning users on single PCs
MSI Afterburner provides a live overlay plus direct GPU clock, voltage, and fan curve control, which supports rapid tuning feedback loops. NZXT CAM also combines local CPU and GPU telemetry with device control for builders who want overlay verification during games.
Lab teams capturing repeatable host telemetry
HWiNFO and Open Hardware Monitor support per-sensor telemetry capture with configurable polling interval and logging scope to standardize test runs. HWMonitor can also help for quick sensor checks when structured capture and deep filtering are not the priority.
Ops teams needing continuous visibility and retention across many hosts
Netdata is built around agent-based collection, streaming time-series graphing, and retention with alert conditions. This supports cross-host monitoring patterns that single-host tools like HWiNFO and AIDA64 do not target by default.
Troubleshooting teams correlating GPU load to processes
NVIDIA App provides process-level GPU attribution inside its NVIDIA driver telemetry view for linking GPU activity to specific running processes. MangoHud delivers per-process overlays for local inspection during benchmarking or gameplay runs.
Desktop and workstation debugging focused on stable hardware history
AIDA64 emphasizes sensor history logging tied to a stable hardware inventory layout for consistent post-incident review. This fits scenarios where comparing sensor trends across time matters more than per-process attribution.
Common mistakes when buying CPU GPU Monitoring Software
Buyers often select based on overlay visuals and then discover gaps in automation, data capture, or process-level attribution. Other failures come from assuming the same sensor fields appear on all hardware and driver stacks.
Tool capability also varies by where telemetry comes from, since some tools rely on host sensor exposure while others rely on GPU driver telemetry integration.
Choosing a driver-integrated overlay and then needing full host sensor depth
NVIDIA App and AMD Software: Adrenalin Edition focus on driver telemetry and their CPU sensor coverage is limited compared with host telemetry tools. HWiNFO provides broader per-sensor telemetry views across CPU and GPU sensors within a single host tool.
Assuming export and logging exists in the same way across single-host utilities
HWMonitor can export monitoring data but it does not provide a documented API or automation hooks for external monitoring systems. Open Hardware Monitor and HWiNFO include more control over polling cadence and logging scope for consistent time-series captures.
Buying for continuous multi-host monitoring but evaluating it as a local desktop overlay tool
Netdata is designed for continuous host dashboards with built-in historical time-series retention and streaming collectors. CAM and MangoHud are better aligned with local overlays and do not provide the same remote, fleet-style monitoring focus.
Ignoring how first-time setup complexity affects sensor coverage filtering
HWiNFO supports very broad hardware sensor coverage but its configuration screens and data filtering can feel complex during first setup. AIDA64 avoids building a monitoring stack by emphasizing sensor history logging with stable hardware inventory layout.
How We Selected and Ranked These Tools
We evaluated MSI Afterburner, HWMonitor, HWiNFO, and the other eight tools against feature depth and workflow coverage. Features account for 40% of the score, and ease and value each account for 30%.
MSI Afterburner separated itself because it pairs live GPU sensor overlays with direct GPU clock, voltage, and fan curve control in the same workflow. HWiNFO ranked highly when controlled per-sensor polling and structured time-series logging mattered for lab-style telemetry capture.
Frequently Asked Questions About Cpu Gpu Monitoring Software
Which tool is best for per-process GPU attribution during real application runs?
How does HWiNFO differ from HWMonitor for capturing historical time-series sensor data?
When does Open Hardware Monitor outperform tools that focus on dashboards or agents?
What breaks if GPU telemetry coverage is inconsistent across a mixed-vendor PC or server environment?
How do AIDA64 and AIDA64-like desktop monitoring workflows handle sensor history and reporting?
Which tool supports GPU fan curve editing and clock control tied to live monitoring?
How does Netdata’s automation workflow compare with single-host overlays like NZXT CAM or MangoHud?
What are the typical setup differences between host-based sensor logging tools and overlay tools?
When should administrators prefer a centralized monitoring approach over desktop-only monitoring tools?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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