Continue.dev vs GitHub Copilot: Best Setup for Local LLM Coding in 2026

Pros

• Fully open-source (Apache 2.0) — inspect and modify every line
• Connect to any LLM: Ollama, LM Studio, Llama.cpp, OpenAI, Anthropic, Cohere, Gemini
• No data leaves your machine when using local models
• Highly configurable: custom context providers, slash commands, and model routing
• VS Code and JetBrains plugins — works in both major IDEs

Cons

• Quality limited by the local model you run — cannot match GPT-4o/Claude on hard tasks
• More setup required: configure config.json, choose models, tune context providers
• No managed cloud backend — you manage model availability and uptime
• Smaller community than Copilot; fewer tutorials for beginners

Pros

• Zero configuration: install plugin, sign in, start coding
• Frontier model quality: GPT-4o and Claude 3.5 Sonnet available
• Copilot Chat, Workspace, PR review integrated into GitHub workflow
• Reliable uptime — SLA-backed cloud API, no model cold starts
• Best-in-class inline completion from years of production data

Cons

• Code sent to GitHub/OpenAI servers — not suitable for air-gap requirements
• $10/mo per developer cost adds up for large teams
• No local model support — cloud-only
• Context window fixed by GitHub, not configurable