#finops
2 posts tagged with #finops
Every article below is hand-written, technically reviewed, and focused on finops. Posts cover real-world architecture decisions, code-level implementation patterns, and trade-offs you'll only discover after shipping production systems.
![nvidia gpu graphics card close-up — illustration for article on Local LLM Break-Even Math [2026]: Power,](https://img.kunalganglani.com/images/vzekdneq/production/76beafb78b6f19b7ed6235232857078a023801c2-1200x675.webp?auto=format&fit=max&q=75&w=600)
AI and Machine Learning Local LLM Break-Even Math [2026]: Power, Idle, Depreciation
Most “GPU price ÷ tokens” break-even math is wrong. Here’s a spreadsheetable local LLM total-cost model that includes idle power, utilization, depreciation, failures, and opportunity cost.
AI and Machine Learning Agent Per-Task Cost Calculation [2026]: Retries, Tools, Caching
A spreadsheet-ready expected-cost model for agent workflows that includes retries, tool-call fanout, context growth, and caching. Plus hard budgets you can actually enforce.