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Client Comparison Sheet: Local AI Options

Version: 1.01.26
Audience: Client (Non-Technical-Friendly)

1. Overview

You have several options for running AI locally.
This sheet explains them in plain language so you can choose what fits you.

2. Summary Table (Plain Language)

Option Name What It Feels Like Best For Needs Docker? Automation? Ease of Use
LM Studio (SOP #3) App that looks like a local ChatGPT One person using AI on their own PC No No Easy
Goose Standalone (SOP #5) One app assistant on Windows Non-technical users, simple workflows No No Very Easy
LLM + Goose (SOP #1) AI in a container with a nice UI Users who want UI + extra isolation Yes Limited Medium
Terminal-Only (SOP #2) Text-only window for advanced users Security-focused, technical workflows Yes Limited Harder
Goose + n8n + Agent (SOP #4) AI that can run tasks automatically Teams who want “every X hours do Y” Yes (2 stacks) Yes Medium/Hard

3. Key Questions to Help You Decide

  1. Do you want something that “just works” like an app?

  2. Yes → Look at LM Studio or Goose Standalone.

  3. No, I’m okay with IT or tech help → Container options are possible.

  4. Do you need the AI to run on its own on a schedule (automation)?

  5. Yes → You probably want Goose + n8n + Agent.

  6. No → Any of the simpler options (LM Studio, Goose Standalone, LLM+Goose).

  7. Do you handle extremely sensitive data (medical, legal, “secret”)?

  8. Yes → We will likely recommend the Terminal-only or LM Studio route, with extra privacy controls.

  9. No → Any option can work; we’ll pick based on your workflow and comfort.

  10. How comfortable are you with technology?

  11. Not at all → Goose Standalone is best for you (Windows only).

  12. Somewhat comfortable → LM Studio is a good starting point.
  13. Very comfortable / IT support available → Containers (LLM+Goose or n8n).

4. Hardware Reality (Simplified)

  • If your computer has 8 GB graphics memory or less:

  • We will use a smaller model and keep things light.

  • If your computer has between 8 and 24 GB:

  • You can run medium models comfortably (our usual recommendation).

  • If your computer has more than 24 GB:

  • You can run larger models and more complex tasks if needed.

  • If you have an AMD graphics card:

  • We may need to run mostly on the CPU; NVIDIA generally works better for this use-case.

5. Our General Advice (Client-Facing)

  • Start simple, with LM Studio or Goose Standalone.
  • Move to containers and automation only when you have a clear reason.
  • For very sensitive data, we will recommend extra privacy steps and may avoid UI tools that have unknown telemetry.