AI Fine-Tuning Cost Calculator — GPT, Claude, Llama, Mistral & More (2026)
Training cost, monthly inference, and break-even vs base API for every major model.
Fine-tuning GPT-3.5 custa ~R$46/milhão de tokens. Modelos open-source (Llama, Mistral) em GPU A100: R$6-15/hora. Startups brasileiras podem acessar créditos via BNDES, Embrapii e programas de nuvem (AWS, Google, Microsoft for Startups).
RAG é mais flexível e barato para a maioria dos casos de negócio. Fine-tuning é melhor para adaptar estilo e formato.
Fine-tuned Llama 3.1 8B models regularly match GPT-4o on narrow classification, extraction, and format-adherence tasks in 2026 benchmarks — at 0.5–2% of the API cost. The engineering investment to get there is the real barrier, not model capability.
Training cost estimates based on OpenAI platform published rates, Google Vertex AI pricing, and self-hosted GPU costs from RunPod/Lambda Labs A100 ($2/hr) and A10G ($0.75/hr) instances. Inference costs scaled from tokens-per-second benchmarks by model size.
