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Concrete: TFHE Compiler that converts python programs into FHE equivalent
| Date | Stars |
|---|---|
| 2026-07-24 | 1565 |
| 2026-07-25 | 1565 |
| 2026-07-28 | 1565 |
| 2026-07-30 | 1565 |
| 2026-08-06 | 1565 |
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<p align="center"> <!-- product name logo --> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://github.com/zama-ai/concrete/assets/157474013/d4680525-2371-454e-97d3-ba39c809a074"> <source media="(prefers-color-scheme: light)" srcset="https://github.com/zama-ai/concrete/assets/157474013/95d02fb1-de48-4bb7-b175-d536bb13091c"> <img width=600 alt="Zama Concrete"> </picture> </p> <hr/> <p align="center"> <a href="https://docs.zama.ai/concrete"> 📒 Documentation</a> | <a href="https://zama.ai/community"> 💛 Community support</a> | <a href="https://github.com/zama-ai/awesome-zama"> 📚 FHE resources by Zama</a> </p> <p align="center"> <a href="https://github.com/zama-ai/concrete/releases"><img src="https://img.shields.io/github/v/release/zama-ai/concrete?style=flat-square"></a> <a href="https://github.com/zama-ai/concrete/blob/main/LICENSE.txt"><img src="https://img.shields.io/badge/License-BSD--3--Clause--Clear-%23ffb243?style=flat-square"></a> <a href="https://github.com/zama-ai/bounty-program"><img src="https://img.shields.io/badge/Contribute-Zama%20Bounty%20Program-%23ffd208?style=flat-square"></a> <a href="https://slsa.dev"><img alt="SLSA 3" src="https://slsa.dev/images/gh-badge-level3.svg" /></a> </p> ## About ### What is Concrete **Concrete** is an open-source FHE Compiler that simplifies the use of fully homomorphic encryption (FHE). Built on TFHE technology and leveraging LLVM, Concrete makes writing FHE programs accessible to developers without deep cryptography expertise. #### Key Features - 🚀 Simple Python API for FHE operations - 🔒 Built-in security guarantees - ⚡ GPU acceleration support - 🛠 Automatic parameter selection - 📊 Built-in performance analysis tools - 🔄 Seamless integration with existing Python code Fully Homomorphic Encryption (FHE) enables performing computations on encrypted data directly without the need to decrypt it first. FHE allows developers to build services that ensure privacy for all users. FHE is also an excellent solution against data breaches as everything is performed on encrypted data. Even if the server is compromised, no sensitive data will be leaked. Concrete is a versatile library that can be used for a variety of purposes. For instance, [Concrete ML](https://github.com/zama-ai/concrete-ml) is built on top of Concrete to simplify Machine-Learning oriented use cases. <br></br> ## Table of Contents - **[Getting Started](#getting-started)** - [Installation](#installation) - [A simple example](#a-simple-example) - **[Resources](#resources)** - [Concrete deep dive](#concrete-deep-dive) - [Tutorials](#tutorials) - [Documentation](#documentation) - **[Working with Concrete](#working-with-concrete)** - [Citations](#citations) - [Contributing](#contributing) - [License](#license) - **[Support](#support)** <br></br> ## Getting Started ### System Requirements - Python 3.9 - 3.12 - 8GB RAM minimum (16GB recommended) - x86_64 or ARM64 processor ### Installation We provide multiple installation methods to suit your needs: #### 1. PyPI Installation (Recommended) For CPU-only version: ```shell pip install -U pip wheel setuptools pip install concrete-python ``` For GPU-accelerated version: ```shell pip install -U pip wheel setuptools pip install concrete-python --index-url https://pypi.zama.ai/gpu ``` #### 2. Docker Installation ```shell # CPU version docker pull zamafhe/concrete-python:v2.0.0 # GPU version docker pull zamafhe/concrete-python:v2.0.0-gpu ``` #### Version Matrix | Concrete Version | Python Version | CUDA Support | |-----------------|----------------|--------------| | 2.11.0 | 3.9 - 3.12 | ≥ 11.8 | | 2.0.0 | 3.8 - 3.12 | ≥ 11.8 | | 1.1.0 | 3.8 - 3.10 | ≥ 11.7 | *Find more detailed installation instructions in [this part of the documentation](https://docs.zama.ai/concrete/getting-started/installing)* <p align="right"> <a href="#about" > ↑ Back to top </a>
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Benoit Chevallier-Mames · France
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Antoniu · Zama
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Alex Quint · @zama-ai
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a282681f97df703c, topic:privacy