# I Built a Local LLM Rig to Escape API Bills. Then I Paid OpenAI Again.

> Source: <https://dev.to/hannune/i-built-a-local-llm-rig-to-escape-api-bills-then-i-paid-openai-again-4bi7>
> Published: 2026-06-13 02:19:42+00:00

I run a one-person AI shop. For 2asy.ai's filing pipeline that needs thousands of single-document extractions per cycle, the local rig lost the batch lane and OpenAI Batch won. Per-pipeline, not per-company.

The rule that decided it: no cross-document attention. Each filing gets its own prompt window. No string concatenation. The rule came from a Neo4j rollback I already paid for.

Quick results.

`GGML_CUDA_DISABLE_GRAPHS=1`

keeps llama.cpp alive when graph optimizer segfaults.`googleapis/python-genai`

issue 1984 is not-planned.`gpt-5.4-mini`

): JSONL line-isolated, 50 percent off, 100-doc nano gate in 2.7 min, zero 429s, around 1 cent per document.The local rig stays for live serving, ER API LLM gate, multimodal, and ablations. The batch lane moves to OpenAI.

Full retrospective with the side-by-side table: [https://hannune.ai/blog/local-llm-to-openai-batch.html](https://hannune.ai/blog/local-llm-to-openai-batch.html)