# Sustainability-first

"Sustainable AI" is doing a lot of marketing work right now. This page
describes what the phrase means inside LowRouter — concretely, what
we measure, what we report, and what we have decided not to claim.

## What we measure

For every inference request, we estimate two numbers:

- **Energy per output token** (Wh), derived from the model's active
  parameter count using the
  [EcoLogits methodology](https://ecologits.ai/0.4/methodology/llm_inference/).
- **Grid carbon intensity** (gCO₂e/kWh) for the region the provider
  serves the request from, sourced from the International Energy
  Agency.

The product gives us **gCO₂e per 1,000 tokens** for the request. The
exact formula and the confidence we attach to each estimate are in the
[methodology page](../sustainable-ai/methodology).

These numbers are exposed:

- On every API response, in an `eco` block.
- On the dashboard, aggregated by day, model, provider, and region.
- On the public model browser, as a comparable estimate per model.

## What we don't measure (yet)

- **Training emissions.** We report inference only. Training is a
  separate, larger, and harder-to-attribute footprint, and folding it
  into per-request numbers is misleading.
- **Hardware embodied carbon.** GPU manufacturing has a real footprint;
  we don't yet have a defensible per-token number for it.
- **Real-time grid mix.** We use annual averages by region. Live
  carbon-aware routing is a future feature, not a current one.
- **Embedding workloads.** Encoder-only models have a different compute
  profile and our formula does not yet model them well.

We list these limits because they are part of what an honest number
looks like. The sustainable-AI page repeats them next to every chart.

## Constraints that fall out of this position

A few platform decisions follow from taking energy and carbon
seriously:

- **The site itself is on a tight transfer budget.** Pages like this
  one ship under 100 KB total. The docs site renders server-side with
  no client framework. Heavy interactive widgets are not added without
  a reason.
- **The default route is auto-mode**, not "the largest model." If a
  smaller model can do the job for a fraction of the energy, we'd
  rather it be the default.
- **Providers and regions with very high grid intensity are
  deprioritised** in routing unless explicitly pinned by the caller.
  See [provider routing](../models/routing).
- **We are slower to add features than we'd like.** Every new
  background job, every dashboard widget, every fancy
  visualisation is a per-user energy cost; we add them when they earn
  the cost.

## What this is not

A pledge that any single request is green. A claim that the estimate is
exact. An assertion that running an LLM through LowRouter is
meaningfully better for the planet than running it directly.

What it is: a measured number, an open formula, and a default that
prefers the smaller model and the cleaner grid when other constraints
allow.