Comparison
CodeCarbon vs Green Algorithms
CodeCarbon vs Green Algorithms: Open-source Python library that estimates the carbon emissions of compute. Carbon footprint calculators and HPC energy…
| Field | CodeCarbon Open-source Python library that estimates the carbon emissions of compute. | Green Algorithms Carbon footprint calculators and HPC energy dashboards for computational science. |
|---|---|---|
| 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. | The calculators and dashboards are free to use; the calculator repository carries a Creative Commons Attribution 4.0 International licence, and the project site is licensed CC BY 4.0. |
| Free tier | Yes | Yes |
| Assets covered | ||
| Platforms | On-premise, Cloud | Web, 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 Green Algorithms
Built for research computing teams that need to estimate and report the carbon footprint of computations and HPC jobs, including a lightweight single-user dashboard that needs no admin access. It offers calculators and dashboards rather than production metering, and the methodology is documented for citation in papers, which suits grant and sustainability reporting. The trade-off is that estimates follow the tool's methodology and user-supplied inputs, so operational telemetry and automated rollups need separate integration. Groups wanting per-workload metering or a commercial reporting platform should pair it with those tools.
Read the Green Algorithms listingJudgement is written by the editor. Paid placements never change the ranking or the recorded field values.
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