#software-carbon-intensity-standard
Issues, solutions, and case studies for software-carbon-intensity-standard
Found 5 nodes with this tag: 1 issue · 2 solutions · 2 case studies
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Issues 1
#00170Closed model and API providers do not disclose the data needed to compute a real footprint
Consumer-side tools must assume model architecture and a worldwide-average grid because providers publish almost nothing about model size, hardware, or data-centre efficiency. Every downstream estimate therefore carries wide, irreducible error bars.
Solutions 2
#00171Benchmark models independently on identical hardware and publish a simple comparable efficiency label
Benchmark models on the same hardware for the same tasks, then publish results as star-band ratings on a leaderboard with a shareable label. An ENERGY STAR-style signal makes efficiency legible to non-experts and usable in procurement, pressuring providers to disclose.
#00168Standardize a single comparable carbon metric per unit of software work
Every tool in this space estimates differently, so numbers are not comparable across teams or vendors. A shared specification expresses software carbon as a rate — emissions per functional unit such as a request, user, or training run — so results can be compared and tracked over
Case studies 2
Paris, France
PartialHugging Face, Salesforce, Cohere and Carnegie Mellon University · since 2025 · Global
AI Energy Score, launched in February 2025 at the Paris AI Action Summit by Hugging Face, Salesforce, Cohere and Carnegie Mellon University, benchmarks models on standardised NVIDIA H100 hardware across 10 tasks and ass…
3 sources
Green Software Foundation (a Linux Foundation project) · Global
The Software Carbon Intensity (SCI) specification reached ISO accreditation as ISO/IEC 21031:2024 in Q1 2024. It defines software carbon as a rate: SCI = (E × I) + M per functional unit R, using a rate rather than a tot…
Non-profit foundation funded by member organisations · 2 sources