
easyread
把英文论文读成舒服的中文:本地 PDF 论文翻译、原文对照、边读边问 AI、文献管理。Read English papers in comfortable Chinese.
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Oct 2026
EasyRead translates English academic papers into comfortable Chinese, page by page, with the original alongside and equations re-typeset so they render properly. You can highlight, take notes, ask an AI about the paper, and export citations as GB/T 7714, APA or BibTeX. It can also translate into Japanese, Korean, Spanish, French, German and Italian. MIT licensed.
It runs locally: download an installer, or run from source with Python 3.10+. You pick the translation engine: your Claude Code or Codex subscription (no API key), a paid API like DeepSeek or OpenAI, a free tier like Gemini or Groq, or a fully offline local model through Ollama. Paper text goes to whichever model you choose, and API keys sit in a plaintext config file on disk.
Chinese-speaking grad students and researchers reading English literature are the audience, and for them it's free beyond model costs, which the project puts at cents per paper on DeepSeek. Readers who want layout-perfect bilingual PDFs should compare PDFMathTranslate, which is AGPL licensed.
The catch: it's a student's one-person project that launched in late September 2026 and ships several releases a day. Installers are unsigned on Windows and not notarized on macOS, so expect security warnings, and the Mac build is Apple Silicon only.
Free vs Self-Hosted vs Paid
fully freeFree: Everything. MIT licensed; KaTeX for equations is also MIT.
Self-hosted: Desktop app with a local server on 127.0.0.1. Windows, Apple Silicon macOS and Linux installers, or run from source with Python 3.10+. Library stored as JSON files, no database. A local Ollama model needs roughly a 6.6 GB download for the recommended size.
Paid: None from the project. Translation cost depends on the engine: Claude Code or Codex spend your existing subscription quota; DeepSeek and other APIs bill per token (the project says cents per paper on DeepSeek); Gemini, Groq and a few others have free tiers; local models are free.
Completely free under MIT. Translation costs whatever your chosen model costs, from nothing on a local model to cents per paper on DeepSeek.
What to do by team size
- Solo
- free; use a local model for unpublished papers
- Small team
- free for each researcher
- Medium team
- free, but plaintext API keys on shared machines are a problem
- Large team
- Skip for lab-wide rollout until installers are signed
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License: MIT License
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