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 quality output, less compute waste.
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 promptAny complexity<150ms
Low-energy~65%
Mid-energy~25%
High-energy~10%
Same qualityLess compute
Energy per tier
Low-energy~65%
Simple queries, factual lookups
0.03 Wh
Mid-energy~25%
Analysis, summarization
0.12 Wh
High-energy~10%
Complex reasoning, creative work
1.79 Wh
The difference in energy between tiers is dramatic. So what does this mean for you?
The difference
Side by side, routed AI uses a fraction of the energy for the same quality output.
Single-model approach
Energy per query0.42 - 1.79 Wh
Low-energy models0%
Mid-energy models0%
High-energy models100%
Output qualityBaseline
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%
Output qualitySame
60-85% less energy, same quality output
Because the ChatFuse Orchestrator routes to efficient models first, a single user averaging 80 queries per day saves:
25 kWh
saved per year
60-85%
less energy per query
6 years
of 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
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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