OpenCode

Overview

OpenCode is an open-source AI coding assistant designed for privacy-conscious developers. It provides intelligent code completion, chat, and refactoring with a focus on local processing and data privacy. OpenCode supports multiple AI models and can be configured to work entirely offline with local models.

OpenCode is ideal for developers working with sensitive codebases who need AI assistance without sending code to external servers.

Features

• Local-first architecture — Process code locally for privacy
• Open-source and free — No cost, fully transparent
• Multi-model support — Claude, GPT, local models
• Offline capability — Work without internet
• VS Code extension — Deep VS Code integration
• Privacy guarantees — Code stays on your machine

Installation

VS Code

1. Open VS Code
2. Go to Extensions (Ctrl+Shift+X)
3. Search for "OpenCode"
4. Click Install

Self-Hosted

# Clone the repository
git clone https://github.com/opencode-ai/opencode.git

# Run locally
cd opencode
npm install
npm start

Configuration

Edit ~/.opencode/config.json:

{
  "provider": "ollama",
  "model": "codellama:7b",
  "offline": true,
  "completion": {
    "enabled": true,
    "maxTokens": 512
  }
}

Core Concepts

Local-First

OpenCode prioritizes local processing:

• Code never leaves your machine (when using local models)
• No external API calls required
• Works offline
• Complete data privacy

Model Options

{
  "models": [
    {
      "name": "CodeLlama",
      "provider": "ollama",
      "model": "codellama:7b"
    },
    {
      "name": "DeepSeek Coder",
      "provider": "ollama",
      "model": "deepseek-coder:6.7b"
    }
  ]
}

Examples

Local Completion

# Start Ollama with a code model
ollama run codellama:7b

# OpenCode will use it automatically

Chat

Explain this function and suggest improvements

Pros

• ✅ Privacy-focused with local processing
• ✅ Completely free
• ✅ Works offline with local models
• ✅ Open-source
• ✅ Good for sensitive codebases
• ✅ No API keys required

Cons

• ❌ Requires local model setup
• ❌ Smaller community
• ❌ Less polished than commercial tools
• ❌ Performance depends on local hardware
• ❌ Smaller model capabilities than cloud models

When to Use

• Developers working with sensitive code
• Teams with strict privacy requirements
• Offline development environments
• Developers wanting complete control
• Projects with compliance requirements

Use Cases

Use Case	Why OpenCode
Sensitive Codebases	Complete privacy with local-only processing
Offline Development	Work without internet connection
Compliance Requirements	Code never leaves your machine
Cost-Free Assistance	No API costs with local models

Comparison with Alternatives

Feature	OpenCode	Continue	Roo Code	Copilot
Cost	Free	Free	Free	Paid
Open Source	✅ Yes	✅ Yes	✅ Yes	❌ No
Local-First	✅ Yes	✅ Yes	✅ Yes	❌ No
Offline	✅ Yes	✅ Yes	✅ Yes	❌ No
JetBrains	❌ No	✅ Yes	❌ No	✅ Yes
VS Code	✅ Yes	✅ Yes	✅ Yes	✅ Yes
Privacy	✅ Excellent	✅ Excellent	✅ Excellent	⚠️ Cloud
Learning Curve	Low	Low	Low	Low
Best for	Maximum privacy	Multi-IDE	VS Code focus	Enterprise

Best Practices

1. Set up Ollama first — Install and pull code models before using OpenCode
2. Configure offline mode — Enable offline: true for local-only operation
3. Choose appropriate model — Use codellama:7b or deepseek-coder:6.7b for best results
4. Adjust completion settings — Tune maxTokens for your hardware capabilities
5. Review suggestions carefully — Local models may be less accurate than cloud models

Troubleshooting

Issue	Solution
No completions	Verify Ollama is running with code model loaded
Slow suggestions	Reduce maxTokens or use smaller model
Extension not loading	Check VS Code extension is enabled
Offline mode fails	Ensure no network requests in configuration

Resources

• Official Website
• GitHub
• Documentation