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Head-to-head · AI Model Explainability Software

AIX360 vs DALEX

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score AIX360 #1 in AI Model Explainability Software 9.1/10 Free plan Free plan✓ 2 of 4 features Visit AIX360
DALEX #6 in AI Model Explainability Software 7.4/10 Free plan Free plan✓ 3 of 4 features Visit DALEX

AIX360 leads on 0 checks, DALEX 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 scoreAIX360 · 9.1/10
  • Free planboth
  • Most featuresDALEX · 3 of 4

AIX360 scores higher on our rubric for ai model explainability software: 9.1 against 7.4 out of 10; our editors rank them #1 and #6.

AIX360 is the better fit for teams needing a broad, free XAI toolkit. DALEX is the better fit for teams explaining models across frameworks.

  • AIX360 fits best

    Teams needing a broad, free XAI toolkit

  • DALEX fits best

    Teams explaining models across frameworks

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. How we rank.

Side by side

Feature AIX360 9.1/10 Visit ↗ DALEX 7.4/10 Visit ↗
At a glance
Editor score 9.1 7.4
Ranking #1 in AI Model Explainability Software #6 in AI Model Explainability Software
Best for Teams needing a broad, free XAI toolkit Teams explaining models across frameworks
Pricing model Free Free
Starting price Free plan Free plan
Free plan ✓ ✓
Free trial — —
Deployment Self-hosted Self-hosted
Support Community, Docs Docs
Built for Solo, Small business, Mid-market, Enterprise Solo, Small business, Mid-market, Enterprise
Features AIX360 2/4 · DALEX 3/4
Feature attribution ✓ ✓
Counterfactual explanations ✓ ✓
Fairness analysis Not checked yet ✓ (best)
Audit reports Not checked yet Not checked yet
Specs
Deployment options Self_hosted Self_hosted
Supported model types Tabular, text, image, and time-series data; algorithms include LIME, SHAP, CEM, and model-specific explainers Model-agnostic; examples include scikit-learn, keras, H2O, xgboost, TensorFlow, CatBoost and LightGBM
Our review
Pros
  • Offers local and global methods, including CEM, LIME, and SHAP
  • Includes explainers for tabular, text, image, and time-series data
  • Provides Ecertify plus faithfulness and monotonicity metrics
  • Offers local and global attribution, including SHAP, LIME and Break Down.
  • Supports integrations across R and Python model frameworks.
  • Includes fairness methods and an interactive Arena exploration dashboard.
Cons
  • Self-hosted library, not a hosted commercial service
  • Use requires working with a Python toolkit and its APIs
  • Support channels are limited to community resources and documentation
  • Its self-hosted package approach may require technical setup.
  • The published support channel is documentation.
  • The feature set may be broader than needed for teams seeking a focused tool.
Our verdict

AIX360 is an open-source Python toolkit for practitioners who need to inspect machine-learning models and datasets. Its methods span local and global explanations, direct and post-hoc approaches, and proxy explainability metrics. The…

Read the review →

DALEX is an open-source toolkit for exploring and explaining predictive machine-learning models in R and Python. It is aimed at teams that need model-agnostic methods across different frameworks, from scikit-learn and keras to H2O,…

Read the review →
  1. AIX360AI Model Explainability Software 9.1Free plan
  2. DALEXAI Model Explainability Software 7.4Free plan

Strengths and trade-offs

  • AIX360 — where it wins

    • Offers local and global methods, including CEM, LIME, and SHAP
    • Includes explainers for tabular, text, image, and time-series data
    • Provides Ecertify plus faithfulness and monotonicity metrics

    Where it doesn't

    • Self-hosted library, not a hosted commercial service
    • Use requires working with a Python toolkit and its APIs
    • Support channels are limited to community resources and documentation

  • DALEX — where it wins

    • Offers local and global attribution, including SHAP, LIME and Break Down.
    • Supports integrations across R and Python model frameworks.
    • Includes fairness methods and an interactive Arena exploration dashboard.

    Where it doesn't

    • Its self-hosted package approach may require technical setup.
    • The published support channel is documentation.
    • The feature set may be broader than needed for teams seeking a focused tool.
  • AIX3609.1/10 · Free plan

    A broad, self-hosted Python toolkit for local, global, and time-series model explanations.

    Visit AIX360Full verdict →
  • DALEX7.4/10 · Free plan

    A broad, model-agnostic toolkit for explaining predictive models across R and Python.

    Visit DALEXFull verdict →

More comparisons

All AI model explainability software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update