πΏ AI Training Cost Calculator
Estimate costs and carbon footprint before you train
π Model Configuration
1
8
64
1B
100B
2T
π‘
EcoCompute Insight
On high-end GPUs like RTX 5090, 4-bit quantization for models <3B parameters may increase energy consumption by ~26% due to de-quantization overhead. We recommend using FP16 for better energy efficiency.
π See our benchmark data βπ° Estimated Results
Estimated Cost
$12,500
50 hours Γ 8 GPUs Γ $2.50/hr
Training Time
50 hours
~2.1 days
Carbon Footprint
320 kg COβe
β 2,080 km driven
π‘ Optimization Tip
Using mixed precision (FP16/BF16) could reduce training time by 30-50%.
β
Calibrated on MLPerf benchmarks β’
<5% error margin
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