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Head-to-head · Quant Tools

Portfolio123 vs Qlib

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score Portfolio123 #6 in Quant Tools 8.5/10 Free plan · 30-day trial Free planFree trial✓ 3 of 4 features Visit Portfolio123
Qlib #7 in Quant Tools 8.4/10 Free plan Free plan✓ 2 of 4 features Visit Qlib

Portfolio123 leads on 0 checks, Qlib on 0, and 4 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scorePortfolio123 · 8.5/10
  • Free planboth
  • Free trialonly Portfolio123
  • Most featuresPortfolio123 · 3 of 4

Portfolio123 scores higher on our rubric for quant tools: 8.5 against 8.4 out of 10; our editors rank them #6 and #7.

Portfolio123 is the better fit for investors building factor-based stock systems. Qlib is the better fit for machine-learning quantitative research.

  • Portfolio123 fits best

    Investors building factor-based stock systems

  • Qlib fits best

    Machine-learning quantitative research

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Side by side

Feature Portfolio123 8.5/10 Visit ↗ Qlib 8.4/10 Visit ↗
At a glance
Editor score 8.5 8.4
Ranking #6 in Quant Tools #7 in Quant Tools
Best for Investors building factor-based stock systems Machine-learning quantitative research
Pricing model Free plan + paid Free
Starting price Free plan · 30-day trial Free plan
Free plan ✓ ✓
Free trial 30 days —
Deployment Cloud Self-hosted
Platforms Web Linux, macOS, Windows
Support Docs Community, Docs
Built for Solo, Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Features Portfolio123 3/4 · Qlib 2/4
Strategy backtesting ✓ ✓
Live trade execution ✓ (best) Not checked yet
Paper trading Not checked yet Not checked yet
Historical data access ✓ ✓
Specs
Asset classes Stocks Stocks
Strategy languages Not checked yet Python
Our review
Pros
  • Build multi-factor rankings, stock screens, and buy/sell rules
  • Backtest screens and portfolio strategies with historical data
  • Track strategies and send orders through Interactive Brokers
  • Automates dataset building, model training, portfolio backtesting, and evaluation
  • Supports supervised learning and reinforcement-learning research
  • Modular Python workflows include experiment records and analysis reports
Cons
  • Focused on stocks rather than multiple asset classes
  • Broker connection and order routing are centered on Interactive Brokers
  • Support is listed through documentation
  • Self-hosted deployment requires users to manage their own environment
  • Official dataset is temporarily disabled; alternative data preparation is documented
  • Research workflow is focused on stocks and does not provide verified live trading
Our verdict

Portfolio123 is a web-based investment research platform for investors who want to build, test, and manage rules-based stock strategies. It combines ranking systems, buy and sell rules, multi-factor screening, historical simulations, and…

Read the review →

Qlib is an open-source Python framework for researchers developing and evaluating quantitative investment strategies, particularly those using machine learning. It brings data handling, forecasting, portfolio management, backtesting, and…

Read the review →
  1. Portfolio123Quant Tools 8.5Free plan · 30-day trial
  2. QlibQuant Tools 8.4Free plan

Strengths and trade-offs

  • Portfolio123 — where it wins

    • Build multi-factor rankings, stock screens, and buy/sell rules
    • Backtest screens and portfolio strategies with historical data
    • Track strategies and send orders through Interactive Brokers

    Where it doesn't

    • Focused on stocks rather than multiple asset classes
    • Broker connection and order routing are centered on Interactive Brokers
    • Support is listed through documentation

  • Qlib — where it wins

    • Automates dataset building, model training, portfolio backtesting, and evaluation
    • Supports supervised learning and reinforcement-learning research
    • Modular Python workflows include experiment records and analysis reports

    Where it doesn't

    • Self-hosted deployment requires users to manage their own environment
    • Official dataset is temporarily disabled; alternative data preparation is documented
    • Research workflow is focused on stocks and does not provide verified live trading
  • Portfolio1238.5/10 · Free plan · 30-day trial

    A web-based toolkit for ranking, screening, backtesting, and trading stock strategies.

    Visit Portfolio123Full verdict →
  • Qlib8.4/10 · Free plan

    A flexible Python toolkit for researching and backtesting stock strategies, run on your own infrastructure.

    Visit QlibFull verdict →

More comparisons

All quant tools comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update