Calculate fine-tuning costs for any LLM.
| Provider | Model | Input cost | Output cost | Total/month |
|---|
The Fine-Tuning Cost Calculator takes monthly input and output token volumes and returns estimated per-token and total monthly costs across several providers, including Plugsky, OpenAI, Anthropic, Google, Groq, DeepSeek and Mistral. It is aimed at teams budgeting token-heavy workloads and comparing providers on an identical usage profile. The comparison updates as you change the inputs. Treat the figures as serving-cost estimates based on published rates and confirm provider-specific charges separately.
It estimates monthly serving cost from token volumes. Fine-tuning training charges depend on provider-specific rules such as dataset size, epochs and base model, so confirm those separately with each provider.
Providers usually charge different rates for input and output tokens, with output often costing more. The table prices each column separately so the totals reflect that difference.
The page compares Plugsky, OpenAI, Anthropic, Google, Groq, DeepSeek and Mistral models. Rates change, so verify the current numbers on the live pricing page before committing a budget.
Canonical pricing and plans: plugsky.com/#sec-pricing · Terms · SLA · Docs