AI Fine-Tuning Cost Estimator – OpenAI, Anthropic, Google

AI Fine-Tuning Cost Estimator

Estimate training and inference costs for fine-tuning LLMs on your custom dataset.

Cost by Provider

Provider / ModelTraining CostMonthly InferenceTotal (1st month)

How Fine-Tuning Pricing Works

Most providers charge per-token for training: Total training tokens = examples × avg_tokens × epochs. Inference on fine-tuned models is typically priced the same as or slightly higher than the base model.

Important Notes

  • Client-side processing only — no data sent to server.
  • Pricing is approximate and subject to change. Verify on provider pricing pages.
  • Minimum training set sizes apply: OpenAI requires 10+ examples, recommended 50-100+.
  • Fine-tuning may require data preparation and validation costs not shown here.
  • Free to use with no login/signup required.
  • Report bugs in comments with sample input and expected output.

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