A detailed cost breakdown for self-hosting large language models in 2026, covering three hardware tiers: cloud GPU instances (H200, B200, GB200), dedicated/colocation servers, and personal rigs (RTX 5090, Mac Studio M4 Ultra). Includes real pricing figures, electricity and staffing hidden costs, a comparison against API providers (OpenAI GPT-4.1, Claude 4, Together AI), and a Python TCO formula with break-even analysis. Self-hosting beats frontier APIs at roughly 2M–5M tokens/day, but open-model API providers like Together AI shift that break-even to 50M+ tokens/day. Staffing (20–30% of a senior engineer) is consistently the most underestimated cost.
Table of contents
Table of ContentsWhat Does It Actually Cost to Self-Host an LLM in 2026?Hardware Costs: Cloud GPU vs. Dedicated Server vs. Personal RigThe Hidden Costs: Electricity, Cooling, and MaintenanceSelf-Hosted LLM Costs vs. API Pricing in 2026ROI Framework: How to Calculate Self-Hosting CostsKey Takeaways and RecommendationsSort: