Cloud AI cost optimization is an architecture and purchasing problem, not a negotiation exercise. Four levers move the bill: model and inference selection, discount instruments such as commitments and spot capacity, token and workflow controls, and the elimination of idle GPU hours. Applied together, they attack training and inference spend …
Editorial team 
NVIDIA NIM Savings: When Self-Hosting Beats LLM APIs
A single NVIDIA H100 GPU running a self-hosted NIM container costs roughly $1,950 per month on RunPod at $2.69 per hour, yet serves the same OpenAI-compatible /v1/chat/completions endpoint as GPT-4.1 — which bills $6 per million blended tokens. The crossover where NIM beats every per-token API sits around 300–500 million …
Reasoning Models Cost 15x. Adaptive Depth Saves 60%
Send one complex query to OpenAI o3 and it can burn 10,000 to 50,000 reasoning tokens before emitting a single visible word — all billed at the $60-per-million output rate, all hidden in a thinking block that never appears in the response (source). Reasoning models are the single biggest line-item …