Comparison
CodeCarbon vs Experiment Impact Tracker
CodeCarbon vs Experiment Impact Tracker: Open-source Python library that estimates the carbon emissions of compute. Drop-in tracker for the energy use,…
| Field | CodeCarbon Open-source Python library that estimates the carbon emissions of compute. | 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 | MIT licensed (Code Carbon NGO); install with pip and run locally or on cloud instances. | MIT licensed Python package published on PyPI as experiment-impact-tracker. |
| Free tier | Yes | Yes |
| Assets covered | ||
| Platforms | On-premise, Cloud | 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 CodeCarbon
Fits ML engineers who want per-run emissions estimates embedded in training or inference code with a few lines of Python and no procurement step. The trade-off is what a library can know: results rest on measured CPU, GPU and RAM power combined with regional grid intensity data it ships or fetches, so accuracy follows its calibration and factor sources rather than any provider billing detail, and someone still owns dashboards, upgrades and factor refreshes when it is self-hosted. Organisations needing audited, organisation-wide accounting should feed its output into a reporting platform.
Read the CodeCarbon 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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