Deep Think
Sustainability Insights • Updated Dec 2025The Eco Cost of AI
GPU energy consumption per task. High-fidelity generation is a physical feat—see how Dec 2025's leading models compare.
All tasks
Holistic view of AI energy impact across Dec 2025's leading architectures.
| Mobile Equiv. | |||
|---|---|---|---|
| Flux.1 | Black Forest Labs | 45.00 | 3.8 Charges |
| o1-preview | OpenAI | 42.00 | 3.5 Charges |
| Stable Diffusion 3.5 | Stability AI | 38.20 | 3.2 Charges |
| Llama 3.1 405B | Meta | 15.50 | 1.3 Charges |
| GPT-4o | OpenAI | 12.50 | 1.0 Charge |
| Gemini 1.5 Pro | 11.20 | 0.9 Charges | |
| Claude 3.5 Sonnet | Anthropic | 10.80 | 0.9 Charges |
| Mistral Large 2 | Mistral | 9.80 | 0.8 Charges |
| GPT-4o-mini | OpenAI | 0.80 | 0.07 Charges |
| Gemini 1.5 Flash | 0.40 | 0.03 Charges |
Dec 2025 data shows a decoupling of Intelligence and Energy. Most 'Flash' models now operate under 1Wh per 1k baseline queries.— Global AI Sustainability Report
The Hidden Infrastructure
AI doesn't live in the 'cloud'—it lives in massive data centers that require constant cooling and high-voltage power.
Training GPT-3 = ~500 Metric Tons of CO2
Avg. LLM training uses millions of gallons of water
Green Innovation
Leading companies are working on 'Small Language Models' (SLMs) and specialized hardware (like Groq) to slash energy needs while maintaining high IQ.