aimhubio/aim

Health v2 · maintenance only

Adoption not part of the score

6243 stars · 407 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Aim is an open-source experiment tracker for AI/ML that logs training runs and metadata, with a web UI to compare runs and a Python API to query them programmatically. It integrates with frameworks like PyTorch, TensorFlow, and serves as a TensorBoard/MLflow alternative.

Use cases

• track machine learning training experiments
• compare training runs across hyperparameters
• visualize training metrics like loss and accuracy
• log LLM prompts and AI metadata
• query experiment data programmatically
• replace TensorBoard or MLflow for experiment tracking
• manage MLOps experiment metadata

When to choose

• you need a fast, self-hosted experiment tracker with a rich comparison UI
• you train models with PyTorch, TensorFlow, or Hugging Face and want minimal integration code
• you want to log and query large volumes of training metadata via an API

When to avoid

• you need a fully managed SaaS tracking service with team collaboration out of the box
• your project is not ML/AI related and you just need general metrics monitoring
• you require deep integration with a specific MLOps platform like Weights & Biases

Facets

library · maturity active

data-visualization logging monitoring analytics sdk machine-learning data-science artificial-intelligence data-visualization developer-tools python cross-platform experiment-tracking mlops tensorboard-alternative mlflow-alternative training-runs metadata-tracking pytorch tensorflow linux macos

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