Running Deepseek R1 locally on Apple Silicon using Ollama and OpenWebUI – Quick Start Guide

Model Size Considerations

The performance of Deepseek models largely depends on your available RAM:

• Deepseek R1 8B: Runs smoothly on 16-18GB RAM machines, good balance of performance and resource usage
• Deepseek R1 14B: Operates at slower output speeds but still functional on 16GB RAM; performs significantly better with 32GB RAM
• Deepseek R1 32B: Unable to run on lower ram machines, highly recommend at least 32GB or more RAM.
• General rule: More RAM provides better performance and allows for larger context windows

Prerequisites

• Apple Silicon Mac (M2, M3, M4 series, M1 can work, but it’s pretty slow)
• macOS Sequoia recommended
• RAM requirements:
  • Minimum: 16GB RAM
  • Recommended: 32GB+ RAM
• Sufficient free storage space (approximately 8GB for the model)
• Docker Desktop for Apple Silicon (Download here)
• Ollama (Official website)
• OpenWebUI installed and configured

Step 1: Installing Ollama

1. Visit Ollama’s official website and download the Apple Silicon version
2. Alternative installation via Homebrew:

brew install ollama

Step 2: Installing OpenWebUI

1. Install Docker Desktop for Apple Silicon:
   • Download from Docker’s official website
   • Follow the installation guide for Apple Silicon Macs
   • Verify installation by running docker --version in Terminal
2. Pull and run OpenWebUI:

docker pull ghcr.io/open-webui/open-webui:main
docker run -d -p 3000:8080 -v open-webui:/app/backend/data ghcr.io/open-webui/open-webui:main

Step 3: Installing Deepseek Models

1. Choose your model size based on available RAM:

# For 16GB RAM machines (recommended)
ollama run deepseek-r1:8b

# For 32GB RAM machines or if you need more capabilities
ollama run deepseek-r1:14b
ollama run deepseek-r1:32b

Step 4: Configuration

1. Launch Ollama:
   Either open the desktop app

ollama serve

2. Open OpenWebUI in your browser: http://localhost:3000
3. Initial Setup:
   • On first launch, you’ll be prompted to create an admin account
   • Choose a secure password (this is important even for local installations)
   • After logging in, you’ll see the main chat interface
4. Configure Backend Settings:
   • Click on the settings icon in the left sidebar
   • Navigate to “Backend Settings”
   • Select “Ollama” as your backend type
   • Set the API endpoint to http://localhost:11434
   • Click “Test Connection” to verify
   • Save your settings
5. Model Configuration:
   • Go to the “Models” section in settings
   • Click “Download New Model”
   • Select your preferred Deepseek model based on your RAM:
     • For 16GB RAM: deepseek-coder-8b-instruct
     • For 32GB RAM: deepseek-coder-14b-instruct
   • Configure model parameters:
     • Temperature: 0.7 (default, adjust for creativity vs precision)
     • Context Length:
       • 8B model: up to 8192 tokens
       • 14B model: reduce to 4096 tokens on 16GB RAM
     • Top P: 0.9 (recommended for code generation)

Optimizing Performance

• Close unnecessary applications
• Monitor memory usage using Activity Monitor
• Consider using memory swap if needed:

sudo launchctl limit maxfiles 65535 200000

Troubleshooting

Common Issues and Solutions

• Memory Pressure:
  • Reduce context length
  • Close other resource-intensive applications
  • Monitor memory usage in Activity Monitor
• Slow Response Times:
  • Check CPU/GPU usage
  • Verify no other intensive processes are running
  • Consider reducing model parameters
• Connection Issues:
  • Verify Ollama is running (ollama serve)
  • Check OpenWebUI Docker container status
  • Confirm port availability

Additional Resources and Links

• Ollama:
  • Download page: https://ollama.ai/download
  • Other models you can add: https://ollama.com/library
  • GitHub repository: https://github.com/ollama/ollama
• Docker:
  • Apple Silicon installation: https://docs.docker.com/desktop/install/mac-install/
  • Docker Desktop documentation: https://docs.docker.com/desktop/