Comparison
AI Energy Score vs EcoLogits
AI Energy Score vs EcoLogits: Open leaderboard that rates the energy efficiency of AI models for inference. Open-source library and API for estimating…
| Field | AI Energy Score Open leaderboard that rates the energy efficiency of AI models for inference. | EcoLogits Open-source library and API for estimating the environmental footprint of generative AI inference. |
|---|---|---|
| Pricing model | Free | Free |
| Pricing published | Public pricing | Public pricing |
| Starting price | Free | Free |
| Licensing | Open source | Open source |
| Pricing details | Public leaderboard and submission portal; the project site lists no paid tier or price for using the ratings. | Mozilla Public License 2.0; the Python library, JavaScript library, calculator and hosted API service are released as open-source tools. |
| Free tier | Yes | Yes |
| Assets covered | ||
| Platforms | Web | Web, API, On-premise |
| Region support | Global | Global |
| Compliance | Not stated | Not stated |
| API available | No | Yes |
| Last verified | 2026-10-22 | 2026-10-22 |
Editor's take on AI Energy Score
Aimed at procurement and model-selection teams that want comparable inference energy ratings across models and tasks without running a benchmark programme themselves. Ratings are 1-5 stars per task or model-size class, based on measured GPU energy in watt-hours submitted by developers, so a score reflects the submitted measurement setup rather than your hardware and prompts. It covers inference only and is a public leaderboard, not a metering tool, so production usage tracking needs separate instrumentation. Teams needing training energy or workload-specific attribution should look elsewhere.
Read the AI Energy Score listingEditor'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 listingJudgement is written by the editor. Paid placements never change the ranking or the recorded field values.
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