Comparison

Eco2AI vs Tracarbon

Eco2AI vs Tracarbon: Python library for tracking the CO2 emissions of machine learning models. Python library and CLI that tracks device energy…

AI Energy MonitoringBoth listings verified
Field-by-field comparison of Eco2AI and Tracarbon
FieldEco2AI

Python library for tracking the CO2 emissions of machine learning models.

Tracarbon

Python library and CLI that tracks device energy consumption and estimates carbon emissions.

Pricing modelFreeFree
Pricing publishedPublic pricingPublic pricing
Starting priceFreeFree
LicensingOpen sourceOpen source
Pricing detailsReleased under the Apache License 2.0 and installable from PyPI.Apache 2.0 licensed (LICENSE.txt); installable from PyPI with optional exporter extras.
Free tierYesYes
Assets covered
PlatformsOn-premise, CloudOn-premise, Cloud
Region supportGlobalGlobal
ComplianceNot statedNot stated
API availableNoNo
Last verified2026-10-222026-10-22

Editor's take on Eco2AI

Built for Python ML practitioners who want emissions logged per experiment with a decorator or explicit start and stop calls, writing a local session record with project, duration, power, hardware and country. The trade-off is modelling scope: the CO2 figure combines measured CPU and GPU power with a regional emission coefficient, so it reflects that coefficient and local power draw rather than metered grid supply, and the log stays local, leaving aggregation and reporting to you. It tracks runs, not infrastructure. Teams needing fleet-wide or audited accounting should feed its logs into a reporting platform.

Read the Eco2AI listing

Editor'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 listing

Judgement is written by the editor. Paid placements never change the ranking or the recorded field values.

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