- Rust 61.2%
- C++ 15.2%
- C 13.7%
- TypeScript 9.7%
- CSS 0.2%
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Koharu
ML-powered manga translator, written in Rust.
Getting Started · Docs · Bug reports · Discord
Koharu introduces a local-first workflow for manga translation, utilizing the power of ML to automate the process. It combines the capabilities of object detection, OCR, inpainting, and LLMs to create a seamless translation experience.
Note
Koharu runs its vision models and LLMs locally on your machine to keep your data private and secure.
Note
Support and discussion are available on the Discord server.
Features
- Automatic detection of text regions, speech bubbles, and cleanup masks
- OCR for manga dialogue, captions, and other page text
- Inpainting to remove source lettering from the page
- Translation with local or remote LLM backends
- Advanced text rendering with vertical CJK and RTL support
- Layered PSD export with editable text
GPU Acceleration
Koharu supports CUDA, ROCm / HIP, Metal, and Vulkan. CPU fallback is always available when the accelerated path is unavailable or not worth the setup cost on your system.
CUDA
Koharu supports NVIDIA GPUs on Windows and Linux through CUDA. Ensure you have the latest NVIDIA driver installed.
HIP / ROCm
Koharu supports AMD GPUs on Windows through ROCm and HIP. Ensure you have the latest AMD driver installed.
Metal
Koharu supports Metal on Apple Silicon Macs.
Vulkan
Koharu also supports Vulkan on Windows and Linux as an alternative to CUDA and HIP.
Machine Learning Models
Koharu uses a staged stack of vision and language models instead of trying to solve the entire page with a single network.
Computer Vision Models
Koharu uses multiple pretrained models, each tuned for a specific part of the page pipeline.
Detection and Layout
Koharu uses object detection to find text regions, speech bubbles, and segmentation masks.
OCR
These models recognize source text after detection.
Inpainting
These models remove source lettering before translated text is rendered back onto the page.
Large Language Models
Koharu has a flexible LLM backend that can run locally or connect to a remote API.
General-Purpose Local Models
- LFM 2.5: lfm2.5-1.2b-instruct
- Ministral 3: ministral-3-8b-instruct
- Gemma 4 instruct (QAT): gemma4-e2b-it, gemma4-e4b-it, gemma4-12b-it, gemma4-26b-a4b-it, gemma4-31b-it
- Qwen 3.5: qwen3.5-0.8b, qwen3.5-2b, qwen3.5-4b, qwen3.5-9b, qwen3.5-27b, qwen3.5-35b-a3b
- Qwen 3.6: qwen3.6-27b, qwen3.6-35b-a3b
Uncensored Local Models
- Gemma 4 uncensored: gemma4-e2b-uncensored, gemma4-e4b-uncensored, gemma4-12b-uncensored, gemma4-26b-a4b-uncensored, gemma4-31b-uncensored
- Qwen 3.5 uncensored: qwen3.5-2b-uncensored, qwen3.5-4b-uncensored, qwen3.5-9b-uncensored
- Qwen 3.6 uncensored: qwen3.6-27b-uncensored, qwen3.6-35b-a3b-uncensored
Cloud Providers
Koharu supports hosted APIs from Atlas Cloud, OpenAI, Gemini, Claude, DeepSeek, and OpenRouter.
Machine Translation Providers
For pure machine-translation use cases, Koharu also supports DeepL, Google Cloud Translation, and Caiyun.
OpenAI-Compatible Providers
Koharu supports any provider that implements the OpenAI-compatible API.
Installation
You can download the latest release of Koharu from the releases page.
We provide prebuilt binaries for Windows, macOS, and Linux.
WinGet
On Windows, you can install Koharu with winget:
winget install koharu
Homebrew
On macOS, you can install Koharu with Homebrew:
brew install --cask koharu
Troubleshooting
You can also set the RUST_LOG environment variable to debug or trace to see more verbose logs:
# macOS / Linux
RUST_LOG=debug koharu
# Windows (PowerShell)
$env:RUST_LOG="debug"; koharu.exe
Development
To build Koharu from source, follow the steps below.
Prerequisites
Install dependencies
bun install
Development
bun dev
Build
bun run build
The built binaries are written to target/release.
Sponsorship
If Koharu is useful in your workflow, consider sponsoring the project.
Contributors ❤️
Thanks to all the contributors who have helped make Koharu better!
License
Copyright 2025-2026 Mayo Takanashi and Koharu contributors.
Koharu is licensed under the GNU General Public License version 3 only (GPL-3.0-only).