Captum

captum.ai · checked 14 Nov 2026

#3 · AI Model Explainability Software

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How it plugs in

—Public API

NoOpen source

YesFree tier

Signal on AI Model Explainability Software6.1#3 of 29

Captum is an open-source library for interpreting machine-learning models built on PyTorch.

Pricing

CaptumOpen-source library · Installation via conda or pipFree

As captum.ai lists them, checked 14 Nov 2026.

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Facts

Website: captum.ai
Price: Free tier
Free trial: No
Algorithms and metrics: Beyond attribution methods, Captum includes infidelity and sensitivity metrics to estimate explanation trustworthiness.
Attribution algorithms: Its algorithms help identify features contributing to a model’s output, including Integrated Gradients.
DeepLIFT limitation: The documented DeepLIFT implementation supports the Rescale rule; RevealCancel is not supported in the described implementation.
Distribution: The site documents installation using either conda or pip.
Maintainer: The site footer identifies Meta Platforms, Inc. in its copyright notice.
Model compatibility caveat: Some hook-based methods do not work with functional nonlinearities; JIT models do not support hook-dependent methods.
Parallel models: The FAQ states that DataParallel and DistributedDataParallel models are supported with all model types.
PyTorch models: Captum supports most types of PyTorch models and is intended to require minimal changes to the original neural network.
Research use: Researchers can implement interpretability algorithms and benchmark them against methods in the library.
Supported modalities: The product site says Captum supports interpretability across vision, text, and other modalities.
Who it is for: The stated primary audiences are model developers and interpretability researchers; application engineers are also identified as users.

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