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Data Science AnalyticsTop 10 Best Disk Cache Software of 2026
Ranked shortlist of top disk cache software tools with criteria and tradeoffs for IT teams, covering options like StarWind L2 Cache.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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StarWind L2 Cache is the best fit when read-heavy block workloads in HCI or SAN setups need local RAM and SSD acceleration with controlled cache coherence, whereas PrimoCache is a strong Windows choice for speeding up repeated reads from stable folders, and OpenZFS L2ARC works if you’re on ZFS with repeated reads that a meaningful hot set on SSD can catch.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
StarWind L2 Cache
Cache lifecycle operations let administrators manage cache warmup and device role changes with storage-aware controls.
Best for: Fits when read-heavy block workloads need local acceleration and controlled cache coherence.
Primo Ramdisk
Editor pickAutomatic recreation settings let the RAM disk return after reboot without manual remounting steps.
Best for: Fits when workflows can point file paths to a RAM-backed drive and regenerate data after restart.
PrimoCache
Editor pickPersistent cache storage that carries cached blocks across reboots for fewer cold misses.
Best for: Fits when Windows environments need faster repeated reads from stable directories and can tolerate cache tuning.
Comparison Table
StarWind L2 Cache
enterpriseStorage caching software using RAM and SSDs for hyperconverged and SAN environments.
Cache lifecycle operations let administrators manage cache warmup and device role changes with storage-aware controls.
StarWind L2 Cache is built for storage environments where block I/O dominates and where the cache tier must behave consistently with underlying volumes. Cache placement is tied to cache devices and cache policies, which makes cache sizing and cache directory placement operationally explicit. It also supports controlled cache lifecycle actions so cache warmup and service changes can be managed without guessing.
A key tradeoff is that write activity can reduce cache hit ratio because invalidation and cache coherence work must track changed blocks. It fits environments with stable read-heavy patterns such as VDI boot storms or hosted application file access patterns that repeat at predictable intervals.
- +Block-level caching targets storage I/O rather than application file paths
- +Cache policies give predictable behavior for invalidation boundaries
- +Cache device lifecycle controls support planned maintenance and warmup
- +Supports storage-tier placement across RAM and SSD media
- –Write-heavy workloads can depress cache hit ratio quickly
- –Sizing and policy tuning require careful workload observation
Virtual desktop infrastructure teams
Accelerate VDI boot and logon reads
Faster session startup
Hosted application operators
Speed up recurring database-related reads
Lower read I/O latency
Show 2 more scenarios
Storage administrators
Standardize cache tier deployments
Repeatable cache operations
Uses cache device roles and policy-driven behavior to keep cache behavior consistent across hosts.
DevOps teams
Reduce storage bottlenecks
Higher effective throughput
Targets local read acceleration to relieve I/O contention on shared backends.
Best for: Fits when read-heavy block workloads need local acceleration and controlled cache coherence.
Primo Ramdisk
SMBWindows RAM-disk software that places selected files and workloads in memory.
Automatic recreation settings let the RAM disk return after reboot without manual remounting steps.
Primo Ramdisk is a host-side RAM disk utility that creates a local filesystem backed by memory instead of persistent storage. It includes controls for size, drive letter or mount point behavior, filesystem formatting options, and startup parameters for repeatable mounts after restart. For caching use, it works best when the application reads from and writes to files in a directory that can be pointed at the RAM disk.
A key tradeoff is data loss across reboot unless the workflow includes explicit copy-out to SSD or application-level regeneration. Cache sizing also demands discipline because allocating too much RAM can starve the OS or other services. Primo Ramdisk fits when build systems, log processing, or asset pipelines need a fast scratch tier and can tolerate losing cache contents between sessions.
- +Mounts as a normal drive so apps can use file paths
- +Configurable size and startup parameters for repeatable RAM mounts
- +Fast local filesystem I/O suited for scratch files and hot assets
- +Simple operational model with clear boundaries and minimal integration
- –No built-in cache coherency guarantees across multiple writers
- –RAM allocation can constrain OS memory under load
- –Cache contents disappear after restart unless workflows restore them
- –Limited integration features for orchestrated cache warming
Build and CI engineering teams
Speed up compilation scratch directories
Lower build time variance
Media and asset processing teams
Stage hot thumbnails and transcoding outputs
Higher cache hit rate
Show 2 more scenarios
Database-adjacent operators
Buffer export files for downstream import
Faster batch handoffs
Write export batches to RAM and copy to persistent storage after completion.
Logging and ETL operators
Reduce latency for rolling file writes
Lower I/O bottlenecks
Send short-lived logs and ETL extracts to the RAM drive to cut disk writes.
Best for: Fits when workflows can point file paths to a RAM-backed drive and regenerate data after restart.
PrimoCache
SMBPrimoCache uses RAM and SSD storage to cache disk reads and writes on Windows systems.
Persistent cache storage that carries cached blocks across reboots for fewer cold misses.
PrimoCache acts as a file-system cache driver for Windows volumes and supports cache persistence by storing cached blocks on disk, which reduces cold-start penalties after restart. It also provides cache management controls like cache size allocation and cache directory selection, which helps tune throughput against available memory and SSD space.
A key tradeoff is that write-heavy workloads can spend more time maintaining cache consistency and flushing behavior than read-heavy workloads. It fits when systems repeatedly scan the same media, reuse large assets from local storage, or serve development and build artifacts from directories that stay stable across sessions.
- +Persistent read caching reduces restart cold misses for repeated file access
- +Directory and process targeting limits caching to chosen I/O paths
- +RAM and disk-tier caching can reduce latency for frequent reads
- +Cache size controls support tuning for memory and SSD constraints
- –Write-heavy workloads can see smaller gains due to consistency overhead
- –Windows-only disk caching limits cross-platform deployment options
- –Fine-grained coherence tuning takes careful testing per workload
- –Cache effectiveness depends on stable access patterns over time
Design and media teams
Reopening large assets from local drives
Fewer perceived delays
Software build engineers
Repeated builds in the same workspace
Shorter rebuild cycles
Show 1 more scenario
VFX and content pipelines
Scrubbing timelines using cached footage
Smoother scrubbing
RAM-tier caching keeps frequently accessed blocks ready during repeated playback scrubs.
Best for: Fits when Windows environments need faster repeated reads from stable directories and can tolerate cache tuning.
Linux bcache
enterpriseLinux block-layer caching that uses fast storage as a cache for slower block devices.
Write-back caching with journal-like cache device state and dirty-block tracking inside the block layer.
Linux bcache binds a block device to a slower backing device and adds a cached block layer in the kernel. It provides a write-back mode that stages updates in the cache and a read path that can serve future reads from the cache without changing the upper filesystem.
- +Kernel block-layer caching for SSD cache over HDD backing
- +Write-back mode reduces backing writes for repeated block access
- +Cache metadata stored on the cache device for repeatable reattachment
- +No application changes needed because reads and writes stay block-oriented
- –Tuning cache mode and write behavior requires careful kernel-level understanding
- –Rebuild and consistency work can become noticeable during heavy cache churn
- –Observability depends on kernel debug counters rather than structured reporting
- –Cache invalidation granularity is block-based and can be coarse for workloads
Best for: Fits when block-level caching can stay in-kernel and workloads tolerate cache-coherency boundaries.
LVM Cache
enterpriseLinux Logical Volume Manager caching for placing hot logical-volume data on faster storage.
Block cache implemented as an LVM device-mapper target that attaches to existing LVM volumes without an application rewrite.
LVM Cache provides a block-device cache that sits under storage by using LVM device-mapper targets to accelerate reads and writes. It targets local disk acceleration with a clear separation between the cache pool and the origin volumes, using metadata to track cached blocks.
- +Uses device-mapper and LVM integration for block-level caching under existing filesystems
- +Clear separation of cache pool and origin volumes via LVM configuration
- +Linux-native operational flow using standard system tooling and device activation
- +Supports cache mode behavior that maps to common storage acceleration goals
- –Configuration mistakes can cause confusing performance swings and require careful validation
- –Limited visibility compared with application-level caches that expose hit ratios directly
- –Relies on Linux storage stack behavior and LVM lifecycle discipline
- –Cache persistence and recovery characteristics depend on metadata handling and policy
Best for: Fits when Linux deployments need block-level read acceleration without changing applications.
OpenZFS L2ARC
enterpriseOpenZFS read caching that uses SSDs or NVMe devices as a secondary cache.
L2ARC feeds off ARC hits and selected block streams, so SSD cache content follows ZFS-specific access patterns.
OpenZFS L2ARC adds an SSD-backed secondary cache layer for ZFS ARC metadata and data blocks, with caching behavior driven by the existing ARC selection logic. It is distinct because it persists cache state only in the sense that the device holds cached contents, while coherency remains tied to ZFS dataset semantics.
- +Tight integration with ZFS ARC selection and dataset coherency semantics
- +SSD tier targets read latency reduction for repeated access patterns
- +Controls for L2ARC device sizing and write throttling reduce cache churn
- +Standard ZFS observability via arc stats and device-level status outputs
- –Cache growth and turnover can add write path overhead and internal churn
- –Sizing is workload dependent and can leave L2ARC underutilized if ARC already fits
Best for: Fits when ZFS workloads on slower vdevs show repeated reads and the SSD tier can hold a meaningful hot set.
SoftPerfect RAM Disk
SMBWindows and macOS software that creates RAM disks for temporary files and application data.
Command-line provisioning for creating and managing RAM-backed drive volumes as part of startup and workload scripts.
SoftPerfect RAM Disk is a Windows-focused RAM disk utility that creates block devices backed by system memory. It targets fast local I/O by mapping a RAM-based volume into the OS using standard drive semantics.
- +Creates a standard Windows drive backed by RAM for low-latency file I/O
- +Boot-time persistence options support consistent cache warmup workflows
- +Command-line control enables repeatable provisioning in scripts
- +Configurable size and drive-letter mapping reduces friction in automation
- –Windows-only driver model limits cross-platform disk caching deployments
- –No built-in eviction or coherency logic beyond manual cache invalidation
- –RAM capacity ceiling requires careful sizing to avoid allocation failures
- –No integration for distributed cache coordination across multiple nodes
Best for: Fits when a Windows environment needs a local read cache tier using a RAM-backed volume.
O&O CleverCache
SMBWindows file cache management tool that optimizes system-level memory allocation.
Per-path cache rules combined with persistent cache directory management for stable hot-data reuse.
O&O CleverCache targets disk caching for Windows workloads by intercepting file-system reads and writes and reusing data from a local cache directory. It is built around cache rules and cache sizing controls that let administrators tune hit ratio goals against storage capacity and I/O pressure.
- +Rule-based cache targeting by path to keep caching focused on hot assets
- +Configurable cache sizing limits to reduce runaway growth on busy systems
- +Operational visibility into cache activity for troubleshooting cache hit behavior
- +Local cache persistence keeps frequently used files available after restarts
- –Best results require careful rule tuning to avoid caching cold or transient files
- –Cache coherency depends on application access patterns, which can cause stale reads
Best for: Fits when a Windows site needs predictable local read caching for frequently accessed files.
AMD StoreMI
SMBAMD storage software that combines SSD and hard-drive capacity into a tiered volume.
Hybrid volume creation that tiles hot blocks from SSD onto an HDD-backed namespace using StoreMI’s filter integration.
AMD StoreMI creates a hybrid storage volume by combining an SSD and an HDD so frequently accessed file blocks can be served from faster media. It is implemented as a Windows-side filter and volume management feature that changes where reads land based on access patterns.
- +Hybrid SSD plus HDD volume reduces HDD read latency for repeated file accesses
- +Windows integration uses a filter-style approach instead of requiring application changes
- +Capacity-based tiering keeps large datasets on HDD while speeding hot data
- +Cache sizing and behavior can be tuned through the StoreMI control flow
- –Limited visibility into cache state and eviction behavior compared with enterprise caching stacks
- –Works only within StoreMI’s supported hardware and Windows configuration scope
- –Write paths can still bottleneck on HDD for write-heavy or streaming workloads
- –Cache persistence and failure recovery semantics are not aligned with database-grade expectations
Best for: Fits when a single Windows system needs lower read latency for frequently reused files.
Apache Traffic Server
enterpriseApache Traffic Server is a proxy cache with configurable disk storage for HTTP and related traffic.
ATS supports fine-grained cache behavior using rule-based configuration that matches on URL, headers, and cache-control semantics.
Apache Traffic Server is a high-performance HTTP proxy that includes a local disk cache for repeat request handling at the edge. It is distinct for its event-driven architecture and its configuration-first control via text config files and documented directives.
- +Disk-backed HTTP caching with policy control based on request and response metadata
- +Event-driven proxy core supports high concurrency under cache hit load
- +Config directives allow targeted cache behavior per URL patterns and headers
- +HTTP management endpoint supports runtime inspection of cache and proxy status
- –Operational tuning requires careful cache sizing and refresh policy planning
- –Cache invalidation depends on consistent header and revalidation behavior from origin
Best for: Fits when an HTTP edge proxy needs local disk caching with fine-grained per-request cache policies and measurable throughput.
Conclusion
After evaluating 10 disk cache software, StarWind L2 Cache 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 Disk Cache Software
This buyer’s guide narrows disk cache software to tools that improve read latency or reduce backend I/O by storing cached blocks or file data on disk tiers. Coverage includes StarWind L2 Cache for block-level cache lifecycle controls, Linux bcache and LVM Cache for in-kernel or device-mapper caching, and OpenZFS L2ARC for ZFS-driven SSD tiers.
The selection also includes PrimoCache for persistent Windows read caching, Primo Ramdisk for RAM-backed drive workflows, and O&O CleverCache for per-path caching with a persistent directory. Rounding out the list are SoftPerfect RAM Disk for command-line RAM provisioning, AMD StoreMI for hybrid SSD-to-HDD tiling, and Apache Traffic Server for rule-based HTTP disk caching on metadata.
Disk Cache Software that accelerates I/O with block and file-tiered storage caches
Disk cache software stores frequently accessed data on disk-based cache storage to reduce repeated reads from slower origin devices, with behaviors that range from write-through to write-back and write-around patterns. Some options operate close to the storage stack, like Linux bcache with write-back dirty-block tracking inside the block layer and LVM Cache using a device-mapper target that attaches to existing LVM volumes. Others target filesystem or platform workflows, like OpenZFS L2ARC feeding SSD cache content based on ZFS ARC hits and PrimoCache persisting cached blocks across reboots to cut restart cold misses.
For Windows file-oriented use cases, StarWind L2 Cache focuses on cache lifecycle operations and predictable invalidation boundaries for block-level acceleration. For HTTP workloads, Apache Traffic Server provides rule-based local disk caching that matches request and response metadata so cache refresh and invalidation follow cache-control and header semantics.
Disk cache capabilities that determine latency, correctness, and operational control
Cache acceleration only helps when the cache placement model matches the workload and when invalidation behavior stays correct under change. These features map to the mechanisms each tool uses to keep cached reads fast without turning data correctness into a manual exercise.
The strongest differentiators in this set are cache lifecycle controls for block caches, persistence for restart behavior, and storage-tier integration for platform caches like ZFS ARC-driven L2ARC and kernel block-layer caching.
Cache lifecycle operations and role-aware cache handling
StarWind L2 Cache includes cache lifecycle operations that let administrators manage cache warmup and device role changes with storage-aware controls, which supports predictable behavior during topology updates.
Persistence across reboot to reduce cold-miss bursts
PrimoCache persists cached blocks so restart workflows hit warm data sooner, while Linux bcache relies on kernel-managed cache device state to maintain write-back dirty-block tracking after instability.
In-kernel block-layer write-back behavior with dirty-block state
Linux bcache implements write-back caching with dirty-block tracking inside the block layer, which can reduce backing writes for repeated access patterns at the cost of tuning and consistency boundaries.
Device-mapper or volume-target integration for minimal application change
LVM Cache exposes a block cache as an LVM device-mapper target that attaches to existing LVM volumes, and it separates cache pool configuration from origin volumes so acceleration can be applied without rewriting applications.
Platform-tier integration using existing cache selection semantics
OpenZFS L2ARC feeds SSD cache content from ZFS ARC hits and selected block streams so the SSD tier follows ZFS dataset access patterns rather than treating all reads uniformly.
Cache rule precision for HTTP metadata-driven invalidation
Apache Traffic Server supports fine-grained cache behavior using rule-based configuration that matches on URL, headers, and cache-control semantics, which ties refresh and invalidation to origin metadata.
RAM-backed drive recreation to keep workflows consistent after restart
Primo Ramdisk automatically recreates RAM disk settings after reboot so file-path workflows return without remount steps, while SoftPerfect RAM Disk provides command-line provisioning that scripts creation during startup.
Choose a disk cache model that matches the workload and the correctness boundary
Start with the placement model. Block-level caches like StarWind L2 Cache, Linux bcache, and LVM Cache accelerate storage I/O, while filesystem and filesystem-adjacent solutions like PrimoCache and O&O CleverCache target file paths and access patterns.
Then pick a correctness boundary strategy. Write-back approaches can cut backing writes but require careful validation of dirty-block handling and coherency expectations, while HTTP caches depend on revalidation correctness driven by headers and cache-control semantics.
Select the cache placement layer based on what the workload touches
If acceleration targets block reads and writes under Linux storage stacks, Linux bcache and LVM Cache act inside the kernel or device-mapper layer so applications do not need file-path changes. If acceleration targets Windows file-path workflows, PrimoCache and O&O CleverCache cache chosen directories or per-path rules so the cache placement follows filesystem access.
Match the persistence behavior to restart and warmup expectations
If restart cold-miss bursts harm read latency targets, PrimoCache persistent caching reduces repeat-read penalty after reboot. If cache warming must be orchestrated around device role changes, StarWind L2 Cache cache lifecycle operations provide storage-aware warmup and role-handling controls.
Pick coherency and write policy based on workload write intensity
For repeated reads with tolerable coherency boundaries, Linux bcache write-back dirty-block tracking can reduce backing writes when blocks are rewritten less frequently. For workloads that are write-heavy, StarWind L2 Cache cache hit ratios can depress quickly and write-heavy patterns can shrink the performance gains.
Use platform integration when the platform already defines the hot set
If the environment runs ZFS datasets and slow vdevs, OpenZFS L2ARC uses ZFS ARC hits and selected block streams so SSD content follows ZFS access patterns. If the workload cannot be tied to ZFS ARC selection semantics, a general-purpose block cache like bcache or a directory-target cache like PrimoCache can better align with the observed file access set.
Choose between local drive hybridization and rule-driven application semantics
If a single Windows system needs lower read latency without application changes, AMD StoreMI builds a hybrid volume that tiles hot blocks from SSD onto an HDD-backed namespace using StoreMI’s filter integration. If the workload is HTTP, Apache Traffic Server ties cache refresh and invalidation to request and response metadata so cache behavior follows cache-control and header semantics.
Plan RAM-disk fit for workflows that regenerate data
If cached content can be regenerated and workloads can point at a RAM-backed path, Primo Ramdisk recreates settings after reboot so processes can resume without manual remount steps. If scripting and startup provisioning are the priority, SoftPerfect RAM Disk supports command-line provisioning that creates and manages RAM-backed drive volumes during workload scripts.
Who should use which disk cache approach
Disk cache software fits teams that need faster repeated reads or fewer backend I/O operations without changing every application. The right fit depends on whether the cache integrates at the block layer, follows file-path behavior, or follows platform-defined access selection semantics.
This list includes block caches built for storage stacks, Windows RAM and filesystem-oriented caching tools, and an HTTP edge cache built for metadata-driven cache policies.
Linux storage teams accelerating repeated block reads on SSD tier hardware
Linux bcache and LVM Cache accelerate at the block layer or device-mapper layer and avoid application rewrites by caching at the storage stack.
Windows teams that want local disk-cached reads for stable directories
PrimoCache focuses on persistent cached blocks for chosen directories and processes, while O&O CleverCache applies per-path cache rules plus persistent cache directory management for stable hot-data reuse.
ZFS administrators targeting SSD read latency for repeated access patterns
OpenZFS L2ARC uses ZFS ARC hits and selected block streams so SSD cache content follows ZFS coherency semantics rather than caching reads uniformly.
HTTP edge operators needing deterministic cache behavior under cache-control and header semantics
Apache Traffic Server provides fine-grained cache rule configuration that matches URL, headers, and cache-control semantics so cache refresh and invalidation can follow origin metadata expectations.
Windows workflow owners that can tolerate RAM-backed regeneration after restart
Primo Ramdisk and SoftPerfect RAM Disk mount RAM-backed drives that support normal file-path access, and Primo Ramdisk recreates settings after reboot to reduce restart friction.
Common disk cache failures and how to prevent them
Cache acceleration often fails when the chosen cache model targets the wrong layer or when cache policy is tuned without observing write behavior and invalidation patterns. The tools in this set differ in how they track dirty data, how they persist across restarts, and how they define coherency boundaries.
Missteps also happen when admin workflows are ignored. Some tools provide lifecycle and warmup controls, while others rely on manual invalidation or careful rule tuning to avoid stale reads and low hit ratios.
Expecting write-back block caching to stay beneficial under sustained write-heavy workloads
Linux bcache can incur write-back overhead with dirty-block tracking and rebuild activity during cache churn, and StarWind L2 Cache can depress cache hit ratio quickly when writes dominate.
Using a RAM disk cache without accounting for coherency and multi-writer expectations
Primo Ramdisk has no built-in cache coherency guarantees across multiple writers, so workflows that involve concurrent writers need manual coordination or a cache model with stronger coherency boundaries.
Caching stale HTTP objects because cache rules and origin revalidation signals are inconsistent
Apache Traffic Server cache invalidation depends on consistent cache-control and header revalidation behavior from origin, so mismatched origin semantics can cause stale reads.
Relying on directory-path caching without tuning path scope to exclude transient files
O&O CleverCache requires careful rule tuning to avoid caching cold or transient files, which can reduce effective throughput by spending capacity on data that never reappears.
Configuring device-mapper or cache-device topology without validating performance swings
LVM Cache configuration mistakes can cause confusing performance swings, so origin and cache pool separation needs validation against observed workload changes.
How We Selected and Ranked These Tools
We evaluated StarWind L2 Cache, Primo Ramdisk, PrimoCache, Linux bcache, LVM Cache, OpenZFS L2ARC, SoftPerfect RAM Disk, O&O CleverCache, AMD StoreMI, and Apache Traffic Server using features at 40% weight, ease at 30% weight, and value at 30% weight. StarWind L2 Cache led the ranking because cache lifecycle operations manage cache warmup and device role changes with storage-aware controls, which directly reduces operational uncertainty during topology updates.
StarWind L2 Cache also targets block-level caching for storage I/O rather than file paths, which aligns with its predictable invalidation boundaries for block acceleration. The other tools were graded lower when their standout behavior depended more on restart regeneration, ZFS selection semantics, or rule tuning that can shift cache hit ratio when workload access patterns change.
Frequently Asked Questions About Disk Cache Software
What is the main difference between StarWind L2 Cache and Linux bcache for read acceleration?
How does OpenZFS L2ARC relate to ZFS cache coherence compared with LVM Cache?
Which tool is best when the goal is a RAM-backed cache directory for hot files on Windows?
When is O&O CleverCache a better fit than PrimoCache on Windows file I/O?
What breaks if a block cache needs to survive write-back power loss without guarantees?
How do cache warmup and cache invalidation operations work differently in StarWind L2 Cache?
Which system supports API-like cache control via HTTP configuration rather than disk-level block mapping?
How do admins manage cache state and observability for OpenZFS L2ARC compared with Apache Traffic Server?
Which tool is intended for hybrid SSD plus HDD block access on a single Windows system?
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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