I Priced the Same Inference Workload on 4 GPU Clouds. Egress Was the Catch

This story was originally published on HackerNoon at: https://hackernoon.com/i-priced-the-same-inference-workload-on-4-gpu-clouds-egress-was-the-catch. A reproducible 2026 cost model pricing one inference workload across six GPU clouds, and why egress, not GPU-hours, decides a third of the bill. Check more stories related to programming at: https://hackernoon.com/c/programming. You can also check exclusive content about #gpu, #ai-infrastructure, #cloud-computing, #llm-inference, #cloud-costs, #no-egress-fee-cloud, #mlops, #hackernoon-top-story, and more. This story was written by: @andreasusic. Learn more about this writer by checking @andreasusic's about page, and for more stories, please visit hackernoon.com. Most GPU cloud comparisons stop at dollars-per-GPU-hour, which is only half the bill. Pricing one identical inference workload (1 GPU, 24/7, 30 TB/month egress) across six clouds from their published rates shows egress quietly eating 22–31% of an AWS, Azure, or GCP bill, a line item that's $0 on providers that don't meter it. The real lesson: egress is an architecture decision, not a billing surprise, so model it before you commit.