Overview

This white paper explores the environmental impact of Generative AI (GenAI) and Large Language Models (LLMs) and presents Chata.ai’s sustainable approach to mitigating these effects. As society races to adopt GenAI technologies, the authors highlight the unsustainable energy consumption and carbon emissions tied to large-scale model inference, offering an alternative that maintains performance while drastically reducing environmental costs.

Environmental Costs of GenAI at Scale

The paper opens by illustrating the scale of energy usage required to support GenAI:

• Running LLMs for just 10 million users daily would require 1,000,000 NVIDIA A100 GPUs, consuming 9.6 million kWh/day and emitting ~3,840 metric tons of CO₂ daily — equivalent to the electricity use of 233,000+ homes .

• A projected 36.5% annual growth in GenAI demand from 2025–2030 clashes with an electricity infrastructure growing at less than 1% annually, risking widespread power outages.

Even with next-gen chips like NVIDIA Blackwell promising 25% better efficiency, the paper argues this won’t meaningfully reduce the growing strain on energy resources.

Chata.ai’s Sustainable Alternative

To address this, Chata.ai has developed an inference engine that runs on CPUs instead of GPUs, enabling:

• Over 97% reduction in inference costs

• More than 95% reduction in carbon emissions

Using data tables on pages 7–8, the paper compares optimized LLM implementations to Chata.ai’s CPU-based solution. For example:

• A 13B parameter model for 1,000 users costs ~$62,640/month on GPUs.

• Chata.ai achieves comparable outcomes for just ~$1,500/month — 2.4% of the cost.

• Similarly, carbon emissions drop from 40.05 metric tons/year to ~1.88 metric tons/year per 1,000 users .

A Broader Call to Action

• Recognize that not all tasks require LLMs — simpler, task-specific models can be more efficient.

• Invest in diversified, sustainable infrastructure.

• Promote societal understanding that technological progress must be balanced with ecological responsibility.

Chata.ai urges the tech community to move beyond a one-size-fits-all model, embracing AI solutions that are intelligent, economical, and environmentally viable.