Self-Hosting an LLM Is Rarely Cheaper Than Paying for API Access

A detailed 2026 cost analysis shows that for most teams, calling a commercial LLM API is more economical than running their own open-weight model. API pricing has continued to fall, with leading models now ranging from roughly $1 to $10 per million tokens, and users pay only for what they consume with no idle infrastructure costs. Self-hosting requires renting GPUs at $2–$12 per hour depending on the cloud provider, meaning a single H100 can cost up to $2,000 a month even before accounting for networking, storage, and redundancy. Beyond raw compute, maintaining a reliable self-hosted model demands an estimated 1.5 to 2 full-time engineers, adding $270,000–$550,000 annually in staffing costs alone. Self-hosting only becomes economically viable at sustained volumes of roughly 5–10 million tokens per month, or when compliance rules, latency demands, or data-privacy requirements make third-party APIs unsuitable.