How I cut my AI inference bill by 80% - moving from OpenAI to self-hosted models

Описание и применение

Сокращение ежемесячных расходов на инференс LLM с $490 до $195 за счёт перехода с OpenAI на собственный сервер Hetzner с моделью Qwen 2.5‑72B, что экономит $295 в месяц.

Задача

High monthly cost for OpenAI GPT‑4o inference ($400‑$490/month) driven mainly by output token usage.

Результат

Reduced total monthly cost from $490 to $195, an 80% savings of ~$295/month ($3,540/year).

Рабочий процесс

• Measure current bill and identify cost drivers
• Pick highest‑volume task (e.g., RAG queries)
• Stand up vLLM locally with Qwen 2.5‑72B
• Add LiteLLM as a drop‑in OpenAI‑compatible gateway
• Move 10% of traffic to self‑hosted and compare outputs
• If quality is acceptable, move 100% of traffic
• Set up monitoring for vLLM crashes

Доказательства

My OpenAI bill was $400/month. After moving to self-hosted models on a single Hetzner GPU box, it's $80/month and falling.

Источник

Cost: $1.50/hour for an A100, mostly idle. About $300/month. Same quality as GPT-4o on most of my tasks. Breakthrough.

Источник

Hardware: Hetzner GPU server, 1× A100 80GB on-demand. Effective cost ~$190/month (shared between workloads).

Источник

Saves: ~$295/month = $3,540/year.

Источник