Open-source experiment tracker for machine learning runs and prompts
Aim is an open-source experiment tracker for machine learning work. You add a few lines to a training script and it logs parameters, metrics, images, audio and system resources for every run, then presents them in a local web UI where runs can be compared side by side and filtered by any logged value. It stores metrics efficiently enough that long training runs with millions of steps remain responsive. The same engine is used to track and compare prompts and responses for language model work. It runs locally or self-hosted with no account required, which matters to teams that cannot send training data to a third party.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
ml experiment tracking, training run comparison, prompt evaluation and model debugging
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It is primarily a Python package that logs to local storage and serves a UI on your machine, with an optional self-hosted tracking server for teams. Hosted options exist, but the open-source path keeps everything on your own infrastructure.
Both track experiments. Aim is open source and local-first, which suits privacy-sensitive or air-gapped setups. Hosted alternatives tend to offer more team features, reports and managed convenience for a subscription.
No. It records what happened during training so you can compare runs and find what worked. Training itself stays in your own code, and Aim only observes and stores what you log.
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