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Impact

The right model for
every request.

The ChatFuse Orchestrator analyzes every request and routes it to the most efficient model that can handle it. Same intelligence output, less compute waste.

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Orchestration

Intelligent routing in action

Most AI platforms send every request to their most expensive model, regardless of task complexity. Here is how ChatFuse does it differently.

Your prompt Any complexity
<150ms Orchestrator Classifies & routes
Same intelligence Less compute
Energy per tier

Low-energy

~65%

Simple queries, factual lookups

0.03 Wh

Mid-energy

Moderate tasks~25%

Analysis, summarization

0.12 Wh

High-energy

Complex reasoning~10%

Complex reasoning, creative work

1.79 Wh

The difference in energy between tiers is dramatic. So what does this mean for you?

Energy impact

The difference

Side by side, routed AI uses a fraction of the energy for the same intelligence output.

Single-model approach

Energy per query0.42-1.79 Wh
Low-energy models0%
Mid-energy models0%
High-energy models100%
Model intelligenceBaseline

Every request uses the most power-hungry model

ChatFuse routing

Energy per query0.03-0.24 Wh
Low-energy models~65%
Mid-energy models~25%
High-energy models~10%
Model intelligenceSame

60-85% less energy, same intelligence output

Because the ChatFuse Orchestrator routes to efficient models first, a single user averaging 80 queries per day saves:

25 kWhsaved per year
60-85%less energy per query
6 yearsof daily phone charging

What we measure

  • Energy intensity per request (Wh/query)
  • Routing distribution across model tiers
  • Output quality parity vs. high-compute baseline

What we acknowledge

  • We claim energy intensity reduction, not carbon reduction
  • Actual emissions depend on data center energy sources
  • Our estimates are modeled from academic benchmarks
  • The routing mix shown is a modeled assumption, not measured telemetry
FAQ

Common questions

All estimates on this page are modeled, not measured. Sources: IEA Energy and AI (2025) · arXiv 2505.09598 · arXiv 2510.01889 · arXiv 2509.20241

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