Fine-Tuning Cost Calculator
Calculate the costs of fine-tuning and running your custom LLM models.
When to Fine-Tune
- You have domain-specific terminology or style requirements
- You need consistent formatting or structure in outputs
- Your use case requires specialized knowledge not in base models
- You want to reduce prompt length and save on inference costs
Training Configuration
Total tokens in your training dataset
How many times to train on the full dataset (3-4 recommended)
Expected Inference Usage
Training Cost
$9.00
One-time cost
Monthly Inference
$5.10
10,000 requests
Annual Inference
$61.20
12 months
First Year Total
$70.20
Training + inference
Cost Breakdown
Training Tokens (with epochs)3,000,000
Training Rate$3/1M tokens
Total Training Cost$9.0000
Monthly Input Tokens5,000,000
Monthly Output Tokens3,000,000
Monthly Inference Cost$5.1000
Fine-Tuning Best Practices
- Start with at least 50-100 high-quality training examples
- Use 3-4 epochs - more can lead to overfitting
- Validate your model with a test set before deploying
- Fine-tuning works best for style, format, and tone adjustments
- Consider if prompt engineering can achieve similar results first
- Monitor fine-tuned model performance over time