RealFeedApp 43 configs across 16 providers reveal pricing differences
The tool compares hourly rental rates per gigabyte of memory and FP8 TFLOPs. Calculations reveal that increasing model memory reduces normalized ownership costs.
- Field
- tools and releases
- What they did
- A tool was created to compare hourly GPU rental rates across cloud providers, normalized by VRAM capacity and FP8 computational power. It allows calculating the memory footprint required for running open-weight models and determining the break-even economics for self-hosting.
- Why it matters
- Users find this useful for selecting the most cost-effective cloud provider and evaluating the economic viability of running models locally, avoiding overpayment for excess memory or insufficient compute power.
#gpu#llm#cloud computing#cost analysis#vram
