Comparison
Carbontracker vs Tracarbon
Carbontracker vs Tracarbon: Open-source tool that tracks and predicts energy use and carbon footprint of model training. Python library and CLI that…
| Field | Carbontracker Open-source tool that tracks and predicts energy use and carbon footprint of model training. | Tracarbon Python library and CLI that tracks device energy consumption and estimates carbon emissions. |
|---|---|---|
| Pricing model | Free | Free |
| Pricing published | Public pricing | Public pricing |
| Starting price | Free | Free |
| Licensing | Open source | Open source |
| Pricing details | MIT licensed; installable from PyPI with pip install carbontracker, and the optional pdfreport extra adds PDF report generation. | Apache 2.0 licensed (LICENSE.txt); installable from PyPI with optional exporter extras. |
| Free tier | Yes | Yes |
| Assets covered | ||
| Platforms | On-premise, Cloud | On-premise, Cloud |
| Region support | Global | Global |
| Compliance | Not stated | Not stated |
| API available | No | No |
| Last verified | 2026-10-22 | 2026-10-22 |
Editor's take on Carbontracker
Fits ML teams training on GPU or CPU hosts that want per-run energy and carbon figures plus a forecast of the remaining epochs, with logs and PDF reports for write-ups. The trade-off is attribution and maintenance: consumption is derived from monitored GPU and CPU power and a configured grid intensity, so results follow those inputs rather than provider billing, and it wraps the training script, which means owning the integration and its dependencies. Reporting is run-level, so organisation-wide rollups need another platform. Workloads without visible power telemetry should verify support first.
Read the Carbontracker listingEditor's take on Tracarbon
Suited to teams running workloads on hosts or Kubernetes clusters that want an emissions signal beside existing observability, exported to Prometheus, Datadog or Kubernetes. The trade-off is data provenance: carbon intensity comes from the Electricity Maps API when a key is configured and otherwise from bundled country and cloud-region data, so accuracy and regional coverage depend on that choice, and per-process or per-container figures carry attribution assumptions. Someone must operate the agent and keep factors current. Organisations needing supplier-reported or audited figures should use it alongside provider tools rather than alone.
Read the Tracarbon listingJudgement is written by the editor. Paid placements never change the ranking or the recorded field values.
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