Fine-Tuning Cost Calculator
Estimate the cost of fine-tuning a language model from the dataset token count, number of epochs and the training price per token.
Last reviewed by the Radiatus Cloud team
Estimate the cost of fine-tuning a model from dataset size and epochs.
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Estimate fine-tuning cost
Fine-tuning adapts a pre-trained language model to your data, and most providers charge based on the number of tokens processed during training. This calculator estimates the cost from your dataset size in tokens, the number of epochs, and the training price per million tokens. The total trained tokens equal the dataset size multiplied by the number of epochs, since each epoch passes over the whole dataset once, and the cost scales directly with that total.
Training a one-million-token dataset for three epochs processes three million tokens, costing the per-million rate times three.
Planning a fine-tuning run
Knowing the cost in advance helps you decide how large a dataset and how many epochs are worthwhile. More epochs can improve fit but cost proportionally more and risk overfitting, so there is a balance to strike. The dataset token count is the main driver, so trimming or deduplicating training data reduces cost as well as improving quality.
This estimate covers the training-token charge; providers may add hosting or usage fees for the fine-tuned model separately. All calculation happens locally in your browser.
Notes on these estimates
Because the fine-tuning cost calculator runs entirely in your browser, nothing you enter is uploaded, so you can use it with private data safely. The figures are estimates based on the values you provide and common rules of thumb, so treat them as planning guidance rather than exact measurements, and run the tool as often as you need for free.
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Frequently Asked Questions
How is fine-tuning cost calculated?
It is the dataset token count times the number of epochs, divided by a million, times the training price per million tokens.
Why multiply by epochs?
Each epoch processes the entire dataset once, so training for several epochs multiplies the total tokens processed and the cost.
Do more epochs always help?
Not necessarily. More epochs can improve fit but cost proportionally more and may cause overfitting, so the right number is a balance.
Does this include hosting the model?
No. It estimates the training-token charge. Providers may bill hosting and inference usage of the fine-tuned model separately.
Privacy & Security
Everything runs in your browser; nothing is uploaded.
How to Use
Enter the dataset tokens, epochs and training price.
Disclaimer: This tool is provided "as is" without warranty of any kind. Results are for educational and utility purposes.
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