Training Cost Estimator - AI Model Training Cost
Calculate machine learning training cost in USD based on GPU type, training hours, cloud provider, and data volume. AI economics calculator for budget planning, cloud cost optimization, and infrastructure comparison across AWS, GCP, and Azure.
Training Cost
Cost = (GPU Hours × Rate) + Storage + DataVariables:
- CostTotal training cost (USD)Total training cost (USD)
- GPU HoursNumber of GPU hours (A100/H100)Number of GPU hours (A100/H100)
- RateGPU rental per hour (USD)GPU rental per hour (USD)
- TokensNumber of training tokensNumber of training tokens
How to Use the KalkuLab Training Cost Estimator
- 1
Select Model
Choose the model size (7B, 13B, 70B, etc.).
- 2
Input Data
Enter the number of tokens per epoch and the number of epochs.
- 3
Select GPU
Choose the GPU type (A100, H100, etc.).
- 4
Calculate
Get the estimated training cost.
Examples
Llama 3 70B
Problem:
1B tokens, 3 epochs, A100 (10 hours). What is the cost?
Solution:
- 1.GPU Hours = 10 hours
- 2.Rate = $2.5/hour (A100)
- 3.Cost = 10 × $2.5 = $25
Result:≈ $25 (Cloud A100)
Training Llama 3 70B on 1B tokens costs about $25 on cloud A100.
Frequently Asked Questions
Cloud vs local training?
Cloud is flexible but expensive long-term. Local training requires buying GPUs upfront (capex).
Is QLoRA cheaper?
Yes, QLoRA only fine-tunes adapters, costing roughly 1/10 of full training.