Estimate energy usage, carbon footprint, and costs of AI models with precision
Consider upgrading to NVIDIA H100 GPUs which offer better performance per watt for large-scale AI workloads.
Using INT8 precision instead of FP16 can reduce energy consumption by up to 60% for inference tasks.
Running workloads in regions with renewable energy can reduce your carbon footprint by up to 75%.
Note: Calculations are estimates based on industry averages and academic research. Actual energy consumption may vary based on specific implementations, hardware configurations, and workload efficiency. Carbon intensity values are regional averages.