Local LLM Setup Advisorv0.20260904.60001

A privacy-conscious professional wants to query contracts and research PDFs with a local LLM on a consumer GPU so sensitive text never leaves the machine. The skill recommends a quantized 7B model, a llama.cpp or Ollama setup, and a retrieval pipeline with test queries. It includes hardware checks and a verification note comparing answers against source passages.

A researcher with a standard laptop and no discrete GPU needs offline summarization and drafting support during fieldwork. The skill selects a small 3B-4B model with aggressive quantization and CPU-optimized inference settings. It provides benchmarks, acceptable latency expectations, and fallback workflows for low-memory machines.

A two-person startup wants code completion and refactoring help without per-seat cloud API costs or sending proprietary code to third parties. The skill recommends a code-focused model sized for their family GPU, plus editor integration through an OpenAI-compatible local endpoint. It includes a checklist for context windows, license review, and prompt templates.

A hobbyist wants to run translation, transcription, and chat assistance on a shared home PC used by family members. The skill matches model size to available RAM and VRAM, provides model-switching scripts, and documents privacy boundaries for each family member. It includes a simple usage guide and reset procedure.

A small healthcare or finance team cannot get cloud AI approved but has workstations with consumer GPUs. The skill produces a local inference proof-of-concept, a data-handling checklist, and latency/throughput measurements for stakeholder review. It also lists remaining risks such as model accuracy limits and lack of enterprise monitoring.

Offer fixed-scope engagements that assess a client's hardware and deliver a working local LLM stack with documentation and training. The skill's workflow and checklists provide the repeatable delivery format. Typical projects take one to two weeks and target small teams that cannot use cloud AI.

Sell or lease a mini-PC or workstation preloaded with an optimized local model stack, curated models, and a simple management interface. The advisor skill determines hardware tiers and model recommendations for each price point. Upsell maintenance, model updates, and onboarding sessions.

Package the advisor's checklists, hardware compatibility matrices, and setup scripts into a paid digital library for DIY builders. Each template targets a specific use case such as document Q&A or local coding. Revenue comes from one-time purchases or a low-cost membership with updates.