#2020th of 24 in Desktop AI apps
koharu
Desktop manga translator with local detection, OCR, inpainting and LLM translation
- Stars
- 6.6k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Sep 2026
- Language
- Rust
2,409 on 10 Apr 20266,560 on 30 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
Koharu is a Rust desktop app that translates manga pages in a pipeline of text and bubble detection, OCR, inpainting to remove source text, and LLM or machine translation. Vision models and GGUF LLMs run locally, with optional hosted providers such as OpenAI, Gemini, Claude, DeepL and OpenAI-compatible endpoints. It includes a WebGPU canvas editor for manual cleanup and typesetting, and exports layered PSD.
Who it is for: Manga scanlators and readers who want private, local page translation
Strengths
- Full pipeline in one app: detection, OCR, inpainting, translation, typesetting and layered PSD export
- Runs vision models and GGUF LLMs locally; hosted LLM and MT providers are optional
- GPU backends: CUDA, ROCm/HIP, Metal and Vulkan; no full CUDA SDK install needed
- Handles images, archives and PDFs, with vertical CJK and right-to-left text layout
Weaknesses
- CPU inference is documented as substantially slower than GPU
- Editor canvas needs WebGPU and a current graphics driver even with CPU inference
- Narrow use case: manga translation only, not a general chat or assistant app
- README gives no RAM or VRAM figures; larger local models need extra hardware
What it needs
- GPU optional
- Needs WebGPU-capable graphics driver, Hugging Face model downloads, Rust, Bun and LLVM (build from source only)
- Models: GGUF, Gemma 4, Qwen 3.5/3.6/3.8, Ministral 3, LFM 2.5
Quick answers
Is koharu open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Does koharu need a GPU?
No. It runs on a CPU and can use a GPU when you have one.
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