mrkeyoor.com_
Tue 29 Sept 18:30 UTC
AI Toolsevaluationupdated 10 Sept 2026

koharu review

Koharu is a desktop workspace for translating manga while keeping page detection, OCR, cleanup, translation, and typesetting in one project. It runs vision tools and local language models on the user's machine, can call hosted translation providers, and exports finished pages as PNG or layered PSD files.

+53stars / 7d
Verdict

Our Koharu install took 398 seconds and 925 MB, then its 358-second build failed on missing atk even though all 88 Vitest cases passed. Try the official release if you want one editor for the full manga translation pass and can review every generated page. Source builders should budget for native Linux packages that bun install does not provide.

We ran it

Lab card: what happened when we ran koharuScreenshot of koharu (koharu.rs)
Install✓ · 398s948 packages · 925 MB
Build✗ · 358s
Tests✓ · 19s88 passed · 0 failed of 88 (vitest)
Repo828 files~278,315 lines of source · 18.2 MB · 11 CI workflows

Answers from our run

Does koharu build from source?

Dependencies installed in 398 seconds (948 packages), and the build failed. We cloned commit 8818911 into a clean Debian container with 3 CPUs and no project-specific setup.

Do koharu's tests pass?

Yes: 88 of 88 passed when we ran the project's own test command (vitest). Some failures need services or credentials a bare container does not have.

Who should not use koharu?

Source builders expecting bun install to be sufficient: the development guide lists Rust, Bun, LLVM, and several Linux desktop libraries, and our build stopped on missing atk.

What are the alternatives to koharu?

Manga Image Translator, BallonsTranslator, Comic Translate. Our Koharu install took 398 seconds and 925 MB, then its 358-second build failed on missing atk even though all 88 Vitest cases passed.

Setup2/5398-second install; source build stopped on missing atk
Docs5/5Hardware, providers, editing, export, and source setup are specific
Community5/5Pushed Sep 9 with active issue and pull request work
Maturity3/5Deep workflow, but hardware reports and source setup need care

Who it’s for

Manga translators who want OCR, cleanup, translation, and page composition in one desktop app.
Editors who expect to correct machine output before publishing it.
Users with suitable graphics hardware who want local models and on-device project files.
Teams that need a PSD handoff after preparing pages in Koharu.

Who it’s NOT for

Source builders expecting bun install to be sufficient: the development guide lists Rust, Bun, LLVM, and several Linux desktop libraries, and our build stopped on missing atk.
Air-gapped first launches: the installation guide says native packages come from GitHub, PyPI, or AMD, while model weights come from Hugging Face.
Older or uncertain GPU setups: CUDA 13.0 needs a Turing-class or newer GPU and an R580-series or newer driver, and open reports describe startup failures on specific CUDA and ROCm machines.
Shops that need direct CBZ delivery: issue 1016 says Koharu imports CBZ but currently exports loose PNG or PSD pages.
Anyone expecting unattended output: open reports cover duplicate text detections and failed inpainting, so every page still needs inspection.

Setup reality

Our sandbox installed 948 packages in 398 seconds and used 925 MB. The build then failed after 358 seconds because pkg-config could not find the atk system library or atk.pc. Vitest still passed all 88 tests in 19 seconds.

Release users face first-run downloads for native packages, followed by model downloads when a feature is first used. Hosted translation services need their own credentials; local GGUF translation does not. Provider secrets go into the operating system's credential service.

Source development needs Rust 1.97.1, Bun 1.3.14, LLVM 22.1.8, and platform libraries. GPU support depends on the operating system, driver, and every selected runtime. The canvas requires WebGPU even when model inference falls back to CPU.

Koharu 0.81.10 keeps translation and page editing together

Koharu 0.81.10 combines the jobs that usually bounce between scripts, translation services, and an image editor. It detects text regions and speech bubbles, reads source text with OCR, translates it, removes the original lettering, and lays out the replacement. Projects accept raster images, archives, and PDFs while preserving page order. The English documentation sits beside Japanese and Simplified Chinese editions, so the feature set is explained beyond a screenshot and an install command.

The 18.2 MB checkout held 828 files and roughly 278,315 lines of source in our measurement. That size reflects a Rust desktop application, a WebGPU canvas, documentation, and JavaScript packages in a monorepo. The payoff is continuity: proofreading, paint layers, text fitting, font fallback, vertical CJK, and right-to-left layout all operate on the same project. This is useful when a translator wants machine assistance but still expects an editor to make the final calls.

Three desktop platforms have releases; source work needs native packages

Windows, macOS, and Linux each have release builds, with WinGet and Homebrew instructions for the first two. First launch can take longer while native packages download, and selected model files arrive on first use. Current source work is fussier. The guide names Rust 1.97.1, Bun 1.3.14, LLVM 22.1.8, and Linux packages for GTK, Xdo, SSL, app indicators, SVG handling, CJK fonts, D-Bus, and the keyring.

Our dependency install succeeded, but it was substantial: 948 packages, 925 MB on disk, and 398 seconds. The later build did not complete. That makes the official installers the sensible evaluation path for translators, while contributors need to follow the full platform setup rather than treating bun run build as a self-contained command. The repository has 11 CI workflow files but no Dockerfile, which fits a native desktop application whose graphics and operating-system integration matter.

What happened when we ran it

Our sandbox installed Koharu at commit 8818911 in 398 seconds. The install added 948 packages and occupied 925 MB in a fresh Debian container with 3 CPUs and 8 GB of RAM. The build ran for another 358 seconds, then exited with code 1. Pkg-config reported that it could not find the atk package, the atk.pc file was unavailable in its search path, and PKG_CONFIG_PATH was unset.

That log supports a narrow conclusion: the source build needs a system library our container did not have. It does not show a defect in OCR, translation, or inpainting. Vitest completed separately in 19 seconds and passed all 88 tests with 0 failures. The clean test result covers the available Vitest suite, while the failed application build means we could not judge the finished desktop runtime from this checkout. No timing or quality claim about model inference follows from this run.

Eight hosted model providers make privacy a per-provider choice

The provider guide names 8 hosted language-model services beside local GGUF inference through llama.cpp. Koharu also separates detection, OCR, inpainting, and translation models, with local vision and cleanup options. Provider credentials live in the operating system's secure store, while non-secret settings go in ~/.koharu/config.toml. Once a hosted service is selected, request content goes to that provider under its retention terms.

The 8 GB sandbox did not reach an inference session because the 358-second build failed first. Actual hardware selection has several moving parts: Metal is available on Apple silicon, while CUDA, ROCm, and Vulkan cover different Windows and Linux combinations. CUDA 13.0 requires compute capability 7.5 or newer and an R580-series or newer driver. The editor still needs a working WebGPU adapter when every ML stage runs on CPU.

PSD export stops above 30,000 pixels, and CBZ export is still manual

A finished page can leave Koharu as flat PNG or layered PSD. The PSD path retains the original image, a hidden removal mask, cleanup or paint layers, and editable text layers. It does not preserve every project concept, and the guide says per-layer visibility and opacity are omitted even though the merged preview respects them. Pages over 30,000 pixels on one side cannot be exported as PSD, so the native project directory remains the safest editable source.

Issue 1016 records a sharper publishing limit: Koharu can import CBZ but cannot export a finished project back to CBZ. Users must export loose pages and create the archive elsewhere. Open issue 1069 describes nested detections producing overlapping text blocks, and issue 731 reports inpainting that can leave random lines on a plain background. Those are specific reasons to inspect region boundaries, cleanup, translation, and final exports rather than running a whole chapter unattended.

The September 9 push and 114 open items show active, fast-moving work

GitHub recorded 5,527 stars, 114 combined issues and pull requests, and a last push on September 9, 2026. Of those open items, 107 were issues rather than pull requests. Release 0.81.10 arrived on September 8, after several other 0.81 releases in the same week. The queue includes fixes under review as well as user reports, so the combined number is not a bug count. It shows current maintenance and a steady stream of edge cases across editors, exports, runtimes, and hardware.

Some of those edge cases sit at startup. Issue 1005 describes a CUDA creation failure on one Windows installation, while issue 1052 reports ROCm device detection failures on a particular Linux and AMD setup. The documentation is candid about compatibility matrices and fallback rules, yet the 358-second source-build failure on our box adds another reason to trial one representative machine and chapter first. Koharu is worth that trial for its unified editing workflow, but it has too many hardware and output paths to approve from a feature checklist alone.

Alternatives

ProjectWhat it isPick it when
Manga Image TranslatorAn automated manga and image translation pipeline with several model and service choices.pick this instead when batch automation matters more than a desktop canvas and layered page editing.
BallonsTranslatorA desktop comic translation tool with machine translation and image or text editing.pick this instead when you want to compare another established GUI and its supported languages, models, and editing workflow.
Comic TranslateA comic translation app and browser extension covering images, PDFs, EPUBs, CBRs, and CBZs.pick this instead when browser use or direct work with several comic archive formats matters most.

What people are saying

  1. [github-trending] koharu-rs/koharu
  2. [github-trending] mayocream/koharu

Sources

  1. Koharu repository and README
  2. Koharu 0.81.10 release
  3. Koharu installation guide
  4. Koharu hardware and runtimes guide
  5. Koharu translation provider guide
  6. Koharu development setup
  7. CBZ export request
  8. Nested text detection report

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