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

Description and use

Cut monthly LLM inference costs from $490 to $195 by moving from OpenAI to a self-hosted Hetzner GPU server running Qwen 2.5‑72B via vLLM and LiteLLM, saving $295/month.

Problem

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

Outcome

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

Workflow

• 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

Evidence

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

Source

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

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

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

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