TranslateBooksWithLLMs
Translate full-length books and documents with Ollama, OpenAI (comptatible), Gemini, Mistral, Poe or OpenRouter. Preserves formatting. Resumes where you left o…
What it does
Core capabilities at a glance
- Docx
- Epub
- Gemini
- Gemini API
- Lmstudio
- Local LLM
- Localization Tool
- Mistral
Deep dive
The full breakdown - performance, comparisons, and setup
TranslateBooksWithLLMs
TranslateBooksWithLLMs is a local-AI tool - Translate full-length books and documents with Ollama, OpenAI (comptatible), Gemini, Mistral, Poe or OpenRouter. Preserves formatting. Resumes where you left off. No file size limits.
Overview
A desktop app that translates books, subtitles, and documents with AI - local or cloud. Drop a file, pick a language, get the result.
- No size limit. Process documents of any length - from a single page to thousand-page novels. The intelligent chunking system handles unlimited content while preserving context between segments. - Perfect preservation. Your documents come out exactly as they went in: EPUB formatting, styles, and structure remain intact. SRT timecodes stay perfectly synchronized. Every tag, every timestamp, every formatting detail is preserved. - Resume anytime. Interrupted translation? Pick up exactly where you left off. The checkpoint system saves progress automatically.
- Download the release for your platform (buttons above), or grab it from the releases page. 2. Extract the archive. 3. Run 'TranslateBook.exe' (Windows) or './TranslateBook' (macOS). 4. Open http://localhost:5000 in your browser.
That's it. On first launch, you choose a translation provider:
- Free & local - Install Ollama and pull a model (e.g. 'ollama pull qwen3:14b'). Nothing leaves your machine. - Cloud (often free tier available) - Paste an API key from one of the providers below.
See docs/CLI.md for all options (TTS voices, rates, formats, etc.).
TranslateBooksWithLLMs is open-source, written primarily in Python, with 1,803 GitHub stars under the AGPL-3.0 license. The latest release is v1.4.8 (2026-06-06).
Key capabilities
From the project's documentation:
- Cloud (often free tier available) - Paste an API key from one of the providers below.
How it fits a local-AI stack
TranslateBooksWithLLMs runs on your own hardware, so pair it with a model and a GPU sized to your needs. Use the VRAM calculator to pick a model that fits your card, and see what you can run for hardware guidance. Related local-AI tools in the directory:
Sources
- Source code & docs: hydropix/TranslateBooksWithLLMs
Stats from GitHub, 2026-06-08.
Frequently asked
Quick answers to common questions
What is TranslateBooksWithLLMs?
TranslateBooksWithLLMs is a other tool for local AI workloads. Translate full-length books and documents with Ollama, OpenAI (comptatible), Gemini, Mistral, Poe or OpenRouter. Preserves formatting. Resumes where you left o…
Is TranslateBooksWithLLMs free and open source?
Yes, TranslateBooksWithLLMs has 1,804 GitHub stars and is licensed under AGPL-3.0. You can self-host it for free on macos, windows, web.
What platforms does TranslateBooksWithLLMs support?
TranslateBooksWithLLMs runs on macos, windows, web.
What hardware do I need for TranslateBooksWithLLMs?
The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. TranslateBooksWithLLMs has 1,804 GitHub stars and an active community.
Does TranslateBooksWithLLMs support GPU acceleration?
TranslateBooksWithLLMs supports GPU acceleration via CUDA, Metal, or Vulkan depending on your platform. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.
What are the best alternatives to TranslateBooksWithLLMs?
Popular alternatives include other other tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.
How much does TranslateBooksWithLLMs cost?
TranslateBooksWithLLMs is free-open-source. It is completely free and open source to self-host.
Pairs well with
Complementary tools, models, and hardware
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Configure NEXT_PUBLIC_GISCUS_REPO_ID and NEXT_PUBLIC_GISCUS_CATEGORY_ID at giscus.app to enable.