Best GitHub Copilot Alternatives: Local, Private, Free (2026)

GitHub Copilot costs $10–$39/month and sends your code to Microsoft's servers. These local alternatives give you AI code completion for free, with your code staying on your machine.

4 Free Options
4 Work Offline
3 Open Source

GitHub Copilot revolutionized software development by bringing AI-powered code completion to millions of developers. But at $10–$39/month per developer and with your proprietary code being processed on Microsoft's servers, many teams — especially in enterprise, defense, healthcare, or fintech — can't or won't use it. The open-source community has responded with powerful alternatives: Continue, Tabby, Aider, and Cody all offer comparable (and in some cases superior) coding assistance while keeping your code completely private. These tools integrate with your existing IDE (VS Code, JetBrains, Neovim, Emacs) and connect to local models via Ollama or dedicated code models like DeepSeek Coder and Qwen 2.5 Coder. This guide breaks down your best options for replacing GitHub Copilot with a local, private, and free solution.

Why Switch to a Local GitHub Copilot Alternative?

Enterprise GitHub Copilot costs $39/user/month — for a team of 10 developers, that's $4,680/year. More critically, every line of code you write with Copilot passes through Microsoft's servers. For companies with NDAs, IP concerns, or regulatory requirements (SOC 2, HIPAA, PCI-DSS), this is a non-starter. Local code assistants like Continue + Ollama run entirely on your own hardware. No code leaves your network. No subscription. No vendor dependency. Modern code models like DeepSeek Coder V2 16B and Qwen 2.5 Coder 32B are competitive with Copilot on standard benchmarks.

$0
Monthly cost
100%
Private
No usage limits
Works offline

Feature Comparison: GitHub Copilot vs Local Alternatives

ToolFreeOpen SourceOfflineCPU OnlyInline AutocompleteChat InterfaceCodebase ContextVS CodeJetBrains
Continue logoContinue
Tabby logoTabby
Aider logoAider
Cody logoCody

* All tools in this list are local alternatives that keep your data on your device.

Best GitHub Copilot Alternatives (2026)

#1Continue logo

Continue

Open-source AI code assistant for VS Code and JetBrains IDEs

FreeOpen SourceWorks Offline
Continue is the most popular open-source alternative to GitHub Copilot, with 31,000+ GitHub stars and a rapidly growing community. It integrates natively into VS Code and JetBrains IDEs as a sidebar panel and inline autocomplete, supporting any LLM backend — Ollama for local models, or cloud providers like Anthropic and OpenAI if you prefer. Continue's standout feature is its flexibility: you can configure different models for different tasks (fast autocomplete with a small model, deeper chat with a larger one), create custom slash commands, and build context providers that teach the AI about your specific codebase. For teams wanting GitHub Copilot functionality with full control, Continue is the gold standard.
31,339 GitHub stars·Windows, macOS, Linux (VS Code & JetBrains plugin)
#2Tabby logo

Tabby

Self-hosted AI coding assistant — no code ever leaves your computer

FreeOpen SourceWorks Offline
Tabby is a self-hosted AI coding gateway designed for teams and enterprises. Unlike Continue (which is an IDE plugin), Tabby is a server that you deploy on your own infrastructure (or a developer machine), then connect your IDE to via a plugin. This architecture means all AI processing happens on your server — perfect for companies where all development laptops must route through a central server. Tabby comes with its own fine-tuned code completion models, a web admin interface, detailed usage analytics, and SSO/team management features. It's the most enterprise-ready local Copilot alternative available.
32,860 GitHub stars·Windows, macOS, Linux (self-hosted server)
#3Aider logo

Aider

AI pair programmer in your terminal that edits code across your entire repo

FreeOpen SourceWorks OfflineCPU Only
Aider takes a fundamentally different approach from Copilot. Instead of inline code suggestions, Aider is a command-line AI pair programmer that works with your entire repository. Tell it 'refactor the authentication module', 'add unit tests to this file', or 'fix this bug' and it reads the relevant files, makes changes, and commits them to git — all with your review and approval. This makes Aider exceptional for large-scale refactoring, adding features to existing codebases, and tasks that require understanding multiple files at once. It supports 100+ LLMs including local ones via Ollama, and its 40,000+ star count reflects its popularity among experienced developers.
40,430 GitHub stars·Windows, macOS, Linux (terminal)
#4Cody logo

Cody

AI coding agent with deep codebase understanding and multi-file editing

FreeWorks OfflineCPU Only
Cody by Sourcegraph brings enterprise-grade codebase intelligence to AI-assisted development. Its core differentiator is its deep code graph integration — rather than just reading the file you have open, Cody understands the relationships between all files in your repository. This makes it exceptional for large codebases where a simple autocomplete tool would fail. The VS Code and JetBrains extensions support local LLMs via Ollama, keeping your code private while giving you Cody's superior context awareness. Free for individual developers, with team/enterprise tiers available.

Local vs Cloud: Pros & Cons

Why Go Local

  • Your proprietary code stays on your machine — no legal/IP concerns
  • Free for unlimited usage — no per-developer seats
  • Works on air-gapped networks — perfect for government/defense
  • Use the best code model for each task (flexibility)
  • No usage limits or rate throttling
  • Continue working even when cloud services are down
  • Full auditability — see exactly what data is used

GitHub Copilot Drawbacks

  • Sends your code to Microsoft/GitHub servers
  • Costs $10–$39/user/month
  • Enterprise concerns around IP ownership of AI-assisted code
  • Rate limits during peak usage times
  • No control over model updates or behavior changes

Local Limitations

  • Requires a more powerful machine for the best models (GPU recommended)
  • Initial setup more involved than just installing a VS Code extension
  • Autocomplete latency may be higher without a dedicated GPU
  • Smaller code models may miss context that GPT-4-based Copilot catches

What GitHub Copilot Does Well

  • GitHub Copilot is tightly integrated with GitHub's code knowledge
  • Very fast completions powered by dedicated cloud infrastructure
  • Instant setup — just install the extension
  • GitHub Copilot Chat and workspace features

Bottom Line

GitHub Copilot is excellent but expensive and sends your code to external servers. For individual developers or small teams, Continue + Ollama running DeepSeek Coder or Qwen 2.5 Coder provides comparable autocomplete quality for free. Aider is the best choice for complex, multi-file refactoring tasks. Teams needing enterprise features with full data isolation should evaluate Tabby. With code models improving rapidly, local AI coding assistance is now a genuine alternative to Copilot — not just a compromise.

Frequently Asked Questions About GitHub Copilot Alternatives

What is the best free GitHub Copilot alternative?

Continue is the most popular free alternative, with deep IDE integration and support for any LLM backend. For terminal-based development, Aider is exceptional for large-scale codebase changes. If you need enterprise features with team management, Tabby is the best self-hosted option.

Which local code model should I use?

For code completion, DeepSeek Coder V2 16B and Qwen 2.5 Coder 32B are the best open-source options — both are competitive with GitHub Copilot on standard benchmarks. For chat-based coding assistance, Llama 3.3 70B or DeepSeek R1 are excellent choices. If you have limited hardware, Qwen 2.5 Coder 7B runs well on 8GB RAM.

Is my code private when using Continue with Ollama?

Yes, completely. When you configure Continue to use a local Ollama instance, all processing happens on your machine. No code is sent to any external server. This makes it suitable for proprietary codebases, government projects, and environments with strict data residency requirements.

Can local code assistants handle large codebases?

Aider and Cody are specifically designed for this — they can read and understand multiple files across your entire repository. Continue also supports codebase indexing through its @codebase context provider. For very large codebases (millions of lines), the quality of context retrieval varies, but for most projects these tools handle it well.

Explore More Local Code Assistants Tools

Browse our full directory of local AI alternatives. Filter by features, platform, and more.