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AI Fine-Tuning Cost Calculator

Calculate the cost of fine-tuning AI models like GPT-4o, Llama, and Mistral. Compare with using base API models.

Input Values

Base Model to Fine-Tune*

Choose the model you want to fine-tune

Training Examples*

Number of training examples in your dataset

100100050000

Training Epochs*

Number of passes through the training data

epochs

Monthly Inference Requests*

Expected API calls per month to the fine-tuned model

100010000500000

Avg Tokens per Request*

Average total tokens per API call

tokens

Results

Total Training Tokens

3,000,000 tokens

~1,000 tokens per example × epochs

One-Time Training Cost

$9.00

Main Result

One-time cost to train the model

Monthly Inference Tokens

5,000,000 tokens

Monthly Inference Cost

Main Result

Monthly cost of running the fine-tuned model

First Year Total Cost

$81

Main Result

Training + 12 months of inference

Base Model Annual Cost

$600

Cost of using larger base model without fine-tuning

Annual Savings vs Base Model

$519

Main Result

How much you save by fine-tuning

Cost Reduction

87%

Main Result

Share your results

Fine-tuning lets you customize AI models for your specific use case — improving quality while potentially reducing costs by using a smaller fine-tuned model instead of a larger base model.

This calculator estimates training costs, monthly inference expenses, and compares the total first-year cost against using a larger base model directly.

How It Works

Choose your model — GPT-4o-mini, GPT-4o, or open-source
Set training data — Number of examples and epochs
Enter usage volume — Monthly requests and tokens
Compare costs — Fine-tuned model vs larger base model

Pro Tips

• Fine-tuning GPT-4o-mini can achieve GPT-4o quality at 10x lower inference cost
• Start with 500-1000 high-quality examples — more isn't always better
• 3 epochs is optimal for most tasks — more can cause overfitting
• Consider fine-tuning to eliminate long system prompts — saves tokens on every call

Input Values

Results

How It Works

Pro Tips

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Input Values

Results