Download digiKam for Windows PC v9.1.0 for Windows PC

digiKam 9.1.0 is free, open-source photo management from the KDE community — face recognition, RAW workflow, batch processing and XMP metadata for large...

Features

• Face detection and recognition run entirely on your PC, grouping the same person across thousands of photos with no cloud uploads or subscription.
• Metadata is stored in open standards — XMP sidecars, EXIF and IPTC — so your tags, ratings and captions survive outside digiKam's own database.
• A complete RAW workflow, batch queue manager and image-quality sorting handle professional jobs such as culling a shoot and converting hundreds of files at once.
• Similarity, fuzzy and sketch search plus geolocation mapping make large libraries genuinely findable, including near-duplicate frames and photos by place.
• It is free and open source from the KDE community, works fully offline, and scales from SQLite for home libraries to MySQL for very large collections.

Considerations

• The interface and settings are dense, and new users should expect a learning curve before the library tools feel natural.
• The first scan of a big collection — thumbnails, fingerprints and face detection — is slow and can tax an older PC for hours.
• It is a photo manager first: advanced retouching and local edits still call for a dedicated image editor alongside it.

digiKam 9.1.0, from the digiKam Team within the KDE community, is photo management for people whose collections have outgrown simple folders. It imports photographs into a searchable library and organises them with albums, hierarchical tags, ratings, labels and captions stored in standard XMP and EXIF metadata rather than a locked-in format — so your organising work is never hostage to the program. The library runs on SQLite by default, with MySQL as an option for very large collections, and everything works entirely offline: your photos and face data never leave your PC. It is free and open source under the GPL, with no subscription, account or paid tier.

digiKam's signature tools are serious ones. Face detection and recognition run entirely on your PC, grouping the same person across thousands of shots with no cloud uploads. A full RAW processing workflow built on LibRaw, a batch queue manager for conversions and corrections, and image-quality sorting that flags blurry or poorly exposed frames — surfacing your sharpest frame from a burst — handle professional jobs like culling a shoot and converting hundreds of files at once. Similarity, fuzzy and sketch search find near-duplicate images, and geolocation on a map makes libraries findable by place. This is the tooling commercial library programs charge subscriptions for, delivered in a first-class Qt6-based 64-bit Windows build from KDE's servers — a real release, not an afterthought port.

The costs are density and patience. The interface and settings are dense, and new users should expect a learning curve before the library tools feel natural. The first import of a large library — thumbnails, fingerprints and face scans — can take hours of background work before the clever features pay off, and on a modest PC you will feel those scans. And digiKam is a photo manager first and an editor second: deep retouching still belongs in a dedicated editor, though its own adjustments cover everyday corrections. For photographers and family archivists who want ownership of a large collection without a subscription, digiKam 9.1.0 is the strongest free option on Windows, full stop. It needs Windows 10 or 11 (64-bit), 4 GB of RAM or more (8 GB recommended for large libraries) and about 1 GB for the program, plus space for the library itself.

Get digiKam-9.1.0-Qt6-Win64.exe (version 9.1.0, about 262 MB) from the stable digiKam directory on download.kde.org. This Qt6 64-bit build is the current Windows release; older Qt5 builds are kept only for legacy systems.

Run the installer, approve the Windows prompt and choose an install folder. On first launch, digiKam asks where your photo collections live and which database to use — the default SQLite choice is right for most users.

Add your photo folders and let digiKam build thumbnails, fingerprints and face data in the background — a large library takes a while on first import. Afterwards, confirm the faces it found, add tags, and your whole collection becomes searchable.

Is digiKam available for Windows?

Yes. The Windows build offered here is digiKam-9.1.0-Qt6-Win64.exe, the current 64-bit release built on the Qt 6 framework and published on KDE's official download servers (about 262 MB). It is a first-class Windows release of version 9.1.0, not an afterthought port.

Is digiKam free?

Yes — digiKam is free and open source under the GPL from the digiKam Team in the KDE community, with no subscription, account or paid tier. It also works entirely offline: your photos and face-recognition data never leave your PC.

How do I download digiKam?

Download the Qt6 Windows 64-bit installer — digiKam-9.1.0-Qt6-Win64.exe — from KDE's official download servers; that is the build linked on this page and the one new Windows users should install. Avoid third-party repacks, since the official KDE build is the current 9.1.0 release.

Is digiKam any good?

For large collections, it offers tooling commercial library programs charge subscriptions for: face detection and recognition that run locally, a full RAW workflow, a batch queue manager, image-quality sorting that flags blurry frames, geolocation and similarity search — with metadata kept in open XMP and EXIF standards. The honest cost is a learning curve, and the first scan of a big library (thumbnails, fingerprints, face scans) can take hours on a modest PC.

How do I use digiKam?

Import your photographs into its searchable library, then organise them with albums, hierarchical tags, ratings, labels and captions stored in standard XMP and EXIF metadata. From there you can group faces, develop RAW files, run conversions through the batch queue manager, and find shots by similarity or by place on the geolocation map; SQLite is the default database, with MySQL an option for very large collections.