How much does
LLM fine-tuning
cost in 2026?
Fine-tuning LLM costs depend on base model, dataset preparation, and infra choices.
What you get at each tier.
Bargain ($1k-10k)
$1,000-$10,000
What you get: A LoRA fine-tune of a small model on your existing data. Limited evals.
Trade-offs: Quality, reliability, production deployment.
Mid-market ($15k-50k)
$15,000-$50,000
What you get: Curated dataset + LoRA fine-tune + basic eval set + deployment.
Trade-offs: Multi-model A/B, deep evals, ongoing iteration.
Senior studio ($50k-200k)
$50,000-$200,000
What you get: Full pipeline — dataset, fine-tune, A/B vs frontier, deep evals, production deployment, observability.
Trade-offs: Speed.
Premier ($200k-1M+)
$200,000-$1M+
What you get: Custom fine-tune + serving infrastructure + ongoing iteration + compliance.
Trade-offs: Budget.
Don't forget the add-ons.
- Compute for training (Modal, Replicate, on-prem)
- Inference compute for serving
- Eval costs
- Dataset annotation if needed
- Ongoing iteration cycles
What drives cost most
- Base model size (1B vs 70B)
- Dataset preparation depth
- LoRA vs full fine-tune
- Evals rigor
- Serving infrastructure
Bands aren't
quotes.
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