Comparison
EcoLogits vs Experiment Impact Tracker
EcoLogits vs Experiment Impact Tracker: Open-source library and API for estimating the environmental footprint of generative AI inference. Drop-in…
| Field | EcoLogits Open-source library and API for estimating the environmental footprint of generative AI inference. | Experiment Impact Tracker Drop-in tracker for the energy use, carbon emissions and compute utilization of ML experiments. |
|---|---|---|
| Pricing model | Free | Free |
| Pricing published | Public pricing | Public pricing |
| Starting price | Free | Free |
| Licensing | Open source | Open source |
| Pricing details | Mozilla Public License 2.0; the Python library, JavaScript library, calculator and hosted API service are released as open-source tools. | MIT licensed Python package published on PyPI as experiment-impact-tracker. |
| Free tier | Yes | Yes |
| Assets covered | ||
| Platforms | Web, API, On-premise | On-premise |
| Region support | Global | Global |
| Compliance | Not stated | Not stated |
| API available | Yes | No |
| Last verified | 2026-10-22 | 2026-10-22 |
Editor's take on EcoLogits
Aimed at teams calling hosted generative AI APIs that want per-request footprint estimates without provider cooperation. It applies life-cycle assessment methodology to model API calls and returns energy and greenhouse gas figures through Python and JavaScript libraries, a web calculator and a hosted API. The trade-off is estimation depth: figures are modelled from published methodology and provider parameters rather than measured on provider infrastructure, so accuracy depends on those assumptions and on provider coverage. It covers inference per request; organisation-wide totals and assurance reporting still need a reporting platform.
Read the EcoLogits listingEditor's take on Experiment Impact Tracker
Fits research groups that want a drop-in tracker producing energy, carbon and compute-utilisation logs, an online appendix and a generated carbon impact statement for papers. Hardware support is specific: Linux hosts with Intel RAPL or powergadget interfaces and NVIDIA GPUs, with real-time Californian grid intensity from caiso.com in that jurisdiction. The trade-off is scope: emissions are estimated from logged power and an intensity source, and the tool is research-oriented, so pipelines, dashboards and organisational rollups are not included. Teams outside those hardware or grid constraints should check support before adopting.
Read the Experiment Impact Tracker listingJudgement is written by the editor. Paid placements never change the ranking or the recorded field values.
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