Local LLMs with Ollama on macOS

Setup for a MacBook Pro M4 Pro (24GB) with models stored on the external drive /Volumes/ROG_PRO. Verified on this machine: gpt-oss:20b loads from the drive and generates at ~52 tok/s (Ollama 0.40.14).

brew install ollama      # CLI

Check: ollama -v

Models live in OLLAMA_MODELS. Default is ~/.ollama/models.

mkdir -p /Volumes/ROG_PRO/ollama/models
touch /Volumes/ROG_PRO/ollama/models/.t && rm /Volumes/ROG_PRO/ollama/models/.t   # writable?

If not writable: Finder → drive → Cmd+I → turn off "Ignore ownership". NTFS drives are read-only on macOS; use APFS.

Persistent menu-bar setting: create ~/Library/LaunchAgents/ollama.models.plist:

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0"><dict>
  <key>Label</key><string>ollama.models</string>
  <key>ProgramArguments</key><array>
    <string>/bin/launchctl</string><string>setenv</string>
    <string>OLLAMA_MODELS</string><string>/Volumes/ROG_PRO/ollama/models</string>
  </array>
  <key>RunAtLoad</key><true/>
</dict></plist>

Load it: launchctl load ~/Library/LaunchAgents/ollama.models.plist

• "address already in use" on ollama serve : an instance is already running (menu bar app or brew service) and ignores your env var. Stop it first:

pkill -f ollama; brew services stop ollama 2>/dev/null; lsof -i :11434   # should print nothing

• Drive unplugged : Ollama can't see your models or creates an empty folder. Mount the drive before starting it.
• macOS may ask for Removable Volumes / Full Disk Access for Ollama. Allow it.

OLLAMA_MODELS=/Volumes/ROG_PRO/ollama/models ollama serve

Leave it running; use a second terminal for everything else. Server: http://127.0.0.1:11434.

Useful server variables:

ollama pull gpt-oss:20b        # download
ollama list                    # installed models
ollama run gpt-oss:20b         # interactive chat (/bye to exit)
ollama run gpt-oss:20b "text"  # one-shot
ollama ps                      # loaded models
ollama stop gpt-oss:20b        # unload from RAM
ollama show gpt-oss:20b        # details
ollama cp a b                  # copy/rename
ollama rm gpt-oss:20b          # delete (frees drive space)

Verify storage: ls /Volumes/ROG_PRO/ollama/models/blobs and du -sh /Volumes/ROG_PRO/ollama/models.

Budget about 17–20GB for the model. Q4_K_M costs ~0.6 GB per billion parameters. Speeds below are third-party estimates (modelfit.io), not benchmarks. Only gpt-oss:20b has been measured here (~52 tok/s).

Coding: gpt-oss:20b is the easy choice in Ollama. JetBrains Mellum2.1 12B-A2.5B Thinking is coding-specific but has no Ollama tag (see §8). Avoid: 70B models (~43GB, won't fit), Q8 above 14B, 32B at Q4 (swaps).

Docker:

docker run -d -p 3000:8080 \
  -e OLLAMA_BASE_URL=http://host.docker.internal:11434 \
  -v open-webui:/app/backend/data \
  --name open-webui --restart always \
  ghcr.io/open-webui/open-webui:main

Without Docker (Python 3.11): pip install open-webui && open-webui serve (port 8080).

Open http://localhost:3000, create the local admin account, pick the model. If none appear: Settings → Connections → Ollama URL http://host.docker.internal:11434 (Docker) or http://localhost:11434.

Open WebUI's own data (chats, settings) is on the internal disk, not ROG_PRO.

brew install sst/tap/opencode      # or: npm i -g opencode-ai

Raise the context first. The 4096 default is too small for agent prompts:

OLLAMA_CONTEXT_LENGTH=32768 OLLAMA_MODELS=/Volumes/ROG_PRO/ollama/models ollama serve

32K fits comfortably with gpt-oss:20b. Drop to 16K if memory gets tight.

~/.config/opencode/opencode.json (global) or opencode.json in the project:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "ollama": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ollama (local)",
      "options": { "baseURL": "http://localhost:11434/v1" },
      "models": { "gpt-oss:20b": { "name": "GPT-OSS 20B" } }
    }
  }
}

Run opencode in a project directory, then /models and choose Ollama (local).

A 20B local model handles small edits and questions. It is weaker than hosted models at long multi-step agent work, so review its changes.

• LM Studio : My Models tab → change models directory to the drive.
• llama.cpp (e.g. Mellum2.1):LLAMA_CACHE=/Volumes/ROG_PRO/llama llama-server -hf JetBrains/Mellum2.1-12B-A2.5B-Thinking-GGUF:Q4_K_M
• Hugging Face / MLX :export HF_HOME=/Volumes/ROG_PRO/hf

curl http://localhost:11434/api/chat -d '{"model":"gpt-oss:20b","messages":[{"role":"user","content":"hi"}],"stream":false}'

curl http://localhost:11434/v1/chat/completions -H 'Content-Type: application/json' \
  -d '{"model":"gpt-oss:20b","messages":[{"role":"user","content":"hi"}]}'