Aim

Self-hosted ML experiment tracker with a performant UI for thousands of training runs.

Open SourceSelf HostedOffline Capable
0.0 (0)

About

Aim is an open source, self-hosted experiment tracker for machine learning teams. A Python SDK logs metrics, hyperparameters, images, audio, distributions, and custom metadata from training runs, and a web UI provides explorers for comparing runs with grouping, aggregation, and Python-based querying. The tool is engineered to stay responsive across thousands of runs, a common pain point in this category. Integrations ship for PyTorch Lightning, Hugging Face Transformers, Keras, XGBoost, CatBoost, LightGBM, Optuna, and more than ten other frameworks, and built-in converters import existing logs from TensorBoard, MLflow, and Weights and Biases. A remote tracking server supports centralized multi-host setups, and official Docker images make Kubernetes deployment straightforward. Released under the Apache 2.0 license and requiring Python 3.7 or newer, Aim suits researchers and ML engineers who want experiment tracking on their own infrastructure instead of a hosted commercial service.

Should you use Aim?

Pick it when

Pick Aim when a research group wants a free, self-hosted tracker for hundreds or thousands of runs with a UI that stays fast while comparing them, or wants to move existing TensorBoard, MLflow, or W&B logs onto its own server.

Look elsewhere when

Skip it if you also need a model registry, deployment, or LLM tracing in one tool, since Aim covers tracking only; MLflow or ClearML go wider. The last tagged release was in May 2025, so check recent activity before standardizing on it.

Alternatives to Aim

  • MLflow

    Adds a model registry, evaluation, and prompt management beyond tracking, at the cost of a heavier platform to run and learn.

  • ClearML

    Bundles tracking with orchestration, data management, and serving, so it replaces more tools but is a bigger system to self-host.

  • DVC

    Tracks experiments in Git with no server at all and versions the data too, but compares runs in the CLI or VS Code rather than a web explorer.

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Details

Price
Free
Platform
Local/Desktop
Difficulty
Easy (2/5)
License
Apache-2.0
Added
May 7, 2026

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