Low Code · Minimal Architecture · Historical Backtests
Leave complexity behind and embrace clean, efficient quant development
| Comparison | QuantAI | Qlib |
|---|---|---|
| Code Volume | Very Low | Very High |
| Architecture |
Simple, only three parts: 1. Data download and edits 2. Plug into deep learning 3. Historical backtests |
Very complex, multiple frameworks, hard to understand |
| Code Changes | Very Easy | Change one line, break everything |
| Onboarding | 10-minute onboarding | Weeks to months |
| Asset Coverage | Full Support Just format the data (e.g., crypto) |
Extremely difficult, error-prone |
| Algorithms | Comparable to Qlib | Slightly more than QuandAI |
A lightweight deep learning framework built for quants
Discover alpha factors and feed them into models seamlessly.
Built-in classic and cutting-edge models.
Use time-machine checks to validate model performance.
Free data downloads and pretrained models.
Low-code development with a simple, hackable structure.
Full support for global stocks, futures, and crypto.
High-performance, multi-threaded alpha mining toolkit
Find and extract excess-return factors in the market.
Massive concurrency cuts computation time.
Flexible parameters automatically filter low-quality factors.
Comprehensive performance reports for individual factors.
Supports long-only and long-short factor mining.
Supports factor mining for global stocks, futures, and crypto.