Estimating
How to estimate what a fine-tune costs
A fine-tune costs the GPU-hours of one run, times the price per GPU-hour, times the number of runs you will really make, plus storage.
Fine-tuning on rented GPUs
Answer in brief
10 short entries on the questions people ask around fine-tuning on rented GPUs.
Each opens with its answer, then gives the detail and the terms behind it.
Estimating
A fine-tune costs the GPU-hours of one run, times the price per GPU-hour, times the number of runs you will really make, plus storage.
Method
A LoRA fine-tune trains a small set of added weights and fits on a smaller GPU, while a full fine-tune updates every weight and needs several times more memory.
GPU choice
Rent the smallest current GPU whose memory holds your job, because memory you do not use is billed every hour all the same.
GPU count
Adding GPUs shortens a run but rarely lowers its cost, because you pay for every GPU for every hour and the speed-up is less than the count.
Failed runs
Failed and repeated runs are often the largest part of a fine-tune bill, and no price page lists them.
Storage
Storage is the part of a fine-tune bill that keeps running after the GPU stops: datasets and checkpoints are billed by the gigabyte for as long as they exist.
Pricing models
Rent on demand while you are still finding settings, and price a term only when the GPU will train most hours of a month.
GPU prices
The RTX Pro 6000 is where most LoRA fine-tunes should be priced first: 96 GB on one card, at a lower hourly price than the datacenter GPUs in these tables.
GPU prices
The H200 is the card to price when a fine-tune needs more than a workstation GPU holds: 141 GB on one datacenter GPU, widely listed.
GPU prices
The B200 is the card for a full fine-tune of a large model, and the one where the smallest rental changes the bill most.
Checklists are original editorial guidance. Published prices do not establish availability.
Fine Tune Cost. “Topics.” Content reviewed 12 Nov 2026. https://finetunecost.com/topics