By LLM Hardware team · Methodology ·
Checked 2026-10-13. Author: LLM Hardware team. This site does not store or show Amazon prices. Check current price on Amazon.
Key fact: Open Interpreter’s current docs describe a terminal coding agent with a sandbox and an approval mode. It is provider-agnostic, including a local model.
How we got it: docs.openinterpreter.com, read 2 October 2026. The page says it is built on the Codex harness and that you switch models with /model.
Checked:
Key fact: Do not run it unattended as root. Approval mode is the safety control the docs describe.
How we got it: Same docs: a sandbox decides what is possible, and an approval mode decides when to ask. This guide recommends leaving the ask in place.
Checked:
Key fact: Simple scripted edits can use a 7B Q4 (about 6.2 GB). Multi-step tasks should be planned on a 27–30B Q4 (about 18–20 GB).
How we got it: VRAM formula. Not a measured success rate for computer-use tasks.
Checked:
Methodology — parameter math, quantization bytes, and the source list.
Open Interpreter’s documentation, read 2 October 2026, describes a coding agent in the terminal. You change into a project, run interpreter, and it reads files, edits them, and runs commands. The page says it sits on the Codex harness and stays provider-agnostic: OpenAI, Anthropic, or a local model, switched with /model. A sandbox limits what can run. An approval mode decides when it must ask. That is the product this guide describes. Older writeups that frame it as an unattended desktop puppet are not what these docs say, and this guide does not revive that framing.
The docs say you bring your own model. Ollama or LM Studio is how that stays on the machine. Open WebUI can be the chat door if you do not want to live in the terminal, but the approval story has to remain somewhere you will actually look. A local model does not make a destructive command safer. It only changes where the weights sat when the command was proposed.
A 7B will write a small script and then do something foolish on the third step. It suits “add a health endpoint” style edits inside a repo, with git so you can revert. For a task that chains several commands, use a 27B or Muse Glimmer, and keep the prompt that asks before it escalates. OpenHands is the alternative when you want a project sandbox rather than your real shell. Prefer that when the downside is high.
| Attempt | Model at Q4 | Memory |
|---|---|---|
| One file, you read the diff | K2-Horizon-7B, 6.2 GB | 8–12 GB. Approval stays on. |
| Several steps, still in a repo | Qwen3.8-27B, 18.2 GB, or K2-32B, 21.2 GB | 24 GB minimum. 36 GB if the session is long. |
| Screenshots of the desktop | Muse Glimmer, formula 20 GB, Meta K-quant ~17 GB plus vision | 24–32 GB envelope from Meta’s post. Not a reason to disable approval. Calculator. |
This guide does not recommend a model tier for “control the whole computer while you are away.” That setup does not get a hardware recommendation. If the docs add a fully unattended mode later, this paragraph still stands until a human reviews the command policy.
Run it as your user, on a machine you can reinstall. The Mac mini M5 Pro 24 GB (B0HGGHNQY6) is enough for the 7B and tight for the 27B. The Studio 36 GB (B0HGKSQMX6) is the multi-step tier. Neither listing is a license to disable prompts. A 24 GB GPU is the same fit on Windows, with the same rule.
Mac mini M5 Pro 24 GB on Amazon
ASIN B0HGGHNQY6. Amazon Associates link. The live price is on that page, not locked in here.
Mac Studio M5 Max 36 GB on Amazon
ASIN B0HGKSQMX6. Amazon Associates link. The live price is on that page, not locked in here.
A correction or a hardware question goes to the contact page.