Best GitHub Copilot Alternatives You Can Run Locally (2026)

Why Look for GitHub Copilot Alternatives?

GitHub Copilot is brilliant, but it comes with significant tradeoffs that drive developers to explore local alternatives:

💰 Subscription Fatigue

Copilot costs $10/month individual or $19/month business ($120-228/year). For teams of 10, that's $2,280/year. Local alternatives? Free forever.

🔒 Your Code Stays Private

Every keystroke with Copilot is sent to GitHub/Microsoft servers. This is a dealbreaker for:

• Proprietary codebases and trade secrets
• Client projects under NDA
• Security-sensitive applications
• Regulated industries (finance, healthcare, defense)

With local code assistants, your code never leaves your machine.

📴 Works Offline

Local code AI works on flights, in secure environments, and during internet outages. Once you download a model, you're coding with AI anywhere.

🎛️ Full Control

Choose your model (DeepSeek Coder, Code Llama, Qwen Coder, StarCoder), customize prompts, adjust creativity, and fine-tune on your own codebase. No Microsoft filters or restrictions.

⚡ No Rate Limits

Copilot has hidden throttling during peak times. Local models? Generate as many completions as your hardware allows.

What to Look For in a Local Code Assistant

IDE Integration

Best tools support VSCode, JetBrains IDEs (IntelliJ, PyCharm, etc.), Neovim, and Emacs. Check compatibility with your editor.

Autocomplete Quality

Inline suggestions should be fast (<500ms), accurate, and context-aware. Look for multi-line completions and function generation.

Chat Features

Beyond autocomplete, the best tools offer chat interfaces for refactoring, explaining code, and generating tests.

Model Flexibility

Can you use different models? Best tools support DeepSeek Coder, Code Llama, Qwen 2.5 Coder, StarCoder 2, and more.

Performance

Suggestions should be fast enough not to interrupt your flow. Look for GPU acceleration support for larger models.

The 10 Best Local GitHub Copilot Alternatives

After testing dozens of tools, here are the 10 best local Copilot alternatives in 2026:

1. Continue.dev — Best Overall

Continue is the leading open-source AI code assistant. It's designed as a true Copilot replacement with local LLM support baked in.

Why Continue is #1

• Works with any LLM: Ollama, LM Studio, OpenAI API, Anthropic, or custom endpoints
• Tab autocomplete: Fast inline suggestions like Copilot
• Chat sidebar: Ask questions, refactor code, generate tests
• Codebase awareness: Understands your entire project context
• Multi-IDE: VSCode, all JetBrains IDEs, and Neovim support
• Active development: Weekly updates, responsive maintainers

Quick Setup with Ollama

# 1. Install Ollama
brew install ollama

# 2. Pull a code model
ollama pull deepseek-coder-v2

# 3. Install Continue extension in VSCode
# Search "Continue" in Extensions marketplace

# 4. Configure Continue to use Ollama
# In Continue settings, set:
# Provider: Ollama
# Model: deepseek-coder-v2

Best For

Developers who want the closest Copilot experience with full local control, multi-IDE users, teams wanting self-hosted AI.

View Continue.dev in our directory →

2. Tabby — Best Self-Hosted Solution

Tabby is a self-hosted Copilot alternative with enterprise features. It's designed for teams that want their own private code AI server.

Standout Features

• Self-hosted server: Run your own code completion server on-premises
• Multi-user support: Team-wide code AI with usage analytics
• Repository indexing: Index your codebase for better context
• Model choice: StarCoder, Code Llama, DeepSeek Coder, and more
• Fast inference: Optimized for low-latency completions (<300ms)
• Admin dashboard: Monitor usage, manage users, track metrics

Docker Setup

# Run Tabby server with GPU support
docker run -it \
  --gpus all \
  -p 8080:8080 \
  -v $HOME/.tabby:/data \
  tabbyml/tabby \
  serve --model TabbyML/DeepSeekCoder-6.7B --device cuda

# Access at http://localhost:8080
# Install Tabby VSCode/JetBrains extension and point to server

Best For

Teams, enterprises, developers who want full control over code AI infrastructure, organizations with compliance requirements.

View Tabby in our directory →

3. Cody (Local Mode) — Best Code Intelligence

Cody by Sourcegraph combines autocomplete with deep code intelligence. Their enterprise plan supports self-hosted/local LLMs.

Key Strengths

• Context awareness: Understands your entire codebase, not just open files
• Multi-repo support: Search across multiple repositories
• Advanced refactoring: Suggest architectural improvements
• Test generation: Create comprehensive test suites
• Local LLM support (Enterprise): Run on-premises with your models

Best For

Large codebases, enterprises needing code search + AI, teams already using Sourcegraph.

View Cody in our directory →

4. Fauxpilot — Local Copilot Clone

Fauxpilot is an open-source server that emulates GitHub Copilot's API. Use it with Copilot-compatible editors but with your own models.

Unique Approach

• Copilot API compatible: Works with existing Copilot extensions
• Model flexibility: SalesForce CodeGen, StarCoder, custom models
• Self-hosted: Full control, no external dependencies
• NVIDIA Triton backend: Optimized inference server

Best For

Developers comfortable with Docker, those wanting Copilot API compatibility, GPU users.

View Fauxpilot in our directory →

5. Ollama + Autocomplete Plugins

Use Ollama as your inference backend with community-built autocomplete plugins for your editor.

Popular Plugins

• VSCode: "Ollama Autocoder" extension
• Neovim: ollama.nvim, gen.nvim
• Emacs: ellama, gptel

Quick Setup (VSCode)

# Install Ollama
brew install ollama

# Pull DeepSeek Coder
ollama pull deepseek-coder-v2:16b

# Install "Ollama Autocoder" in VSCode
# Configure model in settings

Best For

Ollama users, Neovim/Emacs enthusiasts, developers who want maximum flexibility.

6. Codeium (Self-Hosted Enterprise)

Codeium offers a free cloud tier, but their enterprise plan supports fully on-premises deployment.

Features

• Free individual tier (cloud-based, but excellent quality)
• Enterprise self-hosted option for teams
• Supports 70+ programming languages
• Fast autocomplete (<200ms typical)

Best For

Individual developers (free cloud tier), enterprises wanting supported self-hosted solution.

7. LocalAI + VSCode Extension

Run LocalAI server with code models and connect via VSCode extensions that support OpenAI API.

Setup

# Run LocalAI with code model
docker run -p 8080:8080 \
  -v $PWD/models:/models \
  localai/localai:latest \
  --models-path /models \
  --context-size 8192

# Use with any OpenAI-compatible VSCode extension
# Point to http://localhost:8080

Best For

Users who want OpenAI API compatibility, Docker enthusiasts, multi-modal AI workflows.

8. Llama Coder

A lightweight Copilot alternative for VSCode specifically designed for Llama models.

Features

• Simple setup with Ollama
• Fast inline completions
• Minimal configuration
• Low resource usage

Best For

VSCode users wanting the simplest local autocomplete setup.

9. Refact.ai (Local Mode)

Refact.ai offers cloud and self-hosted options with code-specific models.

Features

• Self-hosted server option
• Code-specific fine-tuned models
• Fill-in-the-middle completions
• Chat and refactoring tools

Best For

Teams wanting managed self-hosted solution, fill-in-middle editing.

10. CodeGPT (Local LLM Support)

CodeGPT is a popular chat-based AI assistant that supports local LLMs via Ollama and LM Studio.

Features

• Chat interface in your IDE
• Supports Ollama, LM Studio, LocalAI
• Code explanations and generation
• Unit test creation

Best For

Developers who prefer chat over autocomplete, those using multiple LLM providers.

Comparison Table: All 10 Copilot Alternatives

Quick Setup Guide: Continue + Ollama

The fastest way to get local code AI running is Continue + Ollama. Here's the 5-minute setup:

Step 1: Install Ollama

# macOS/Linux
curl -fsSL https://ollama.ai/install.sh | sh

# Or with Homebrew
brew install ollama

# Windows: Download from ollama.ai

Step 2: Pull a Code Model

# Best overall (16B parameters, excellent quality)
ollama pull deepseek-coder-v2:16b

# Or smaller/faster (6.7B, good for laptops)
ollama pull deepseek-coder:6.7b

# Or for low-end hardware (1.3B)
ollama pull qwen2.5-coder:1.5b

Step 3: Install Continue in VSCode

1. Open VSCode
2. Go to Extensions (Cmd/Ctrl + Shift + X)
3. Search for "Continue"
4. Click Install

Step 4: Configure Continue

1. Click Continue icon in sidebar
2. Click the gear icon (settings)
3. Add Ollama configuration:

{
  "models": [
    {
      "title": "DeepSeek Coder",
      "provider": "ollama",
      "model": "deepseek-coder-v2:16b"
    }
  ],
  "tabAutocompleteModel": {
    "title": "DeepSeek Coder",
    "provider": "ollama",
    "model": "deepseek-coder-v2:16b"
  }
}

Step 5: Start Coding!

• Autocomplete: Just start typing — suggestions appear inline
• Accept: Press Tab to accept suggestions
• Chat: Open Continue sidebar, ask questions about your code
• Refactor: Highlight code, right-click → Continue → Refactor

Best Models for Code Completion (2026)

The model matters more than the tool. Here are the current best options:

🏆 Best Overall: DeepSeek Coder V2 (16B)

DeepSeek's latest code model rivals GitHub Copilot quality. Excellent at autocomplete, refactoring, and understanding context.

ollama pull deepseek-coder-v2:16b

⚡ Best Balance: Qwen 2.5 Coder (7B)

Alibaba's code model offers great quality-to-speed ratio. Fast enough for real-time completions, smart enough for complex tasks.

ollama pull qwen2.5-coder:7b

💨 Fastest: Qwen 2.5 Coder (1.5B)

For slower hardware or instant completions, the 1.5B version is surprisingly capable.

ollama pull qwen2.5-coder:1.5b

📚 Best Context: Code Llama (34B)

Meta's largest Code Llama model excels at understanding large codebases. Requires more RAM/VRAM.

ollama pull codellama:34b

🌟 Best Open Source: StarCoder 2 (15B)

Community-favorite model trained on permissively licensed code. Great for commercial use.

ollama pull starcoder2:15b

Hardware Recommendations

Privacy Benefits of Local Code AI

Your Code Never Leaves Your Machine

With Copilot, every keystroke is sent to Microsoft. With local AI, everything processes on your computer. Critical for:

• Proprietary code: Trade secrets stay secret
• Client work: Honor NDAs without compromise
• Security research: Vulnerability analysis without exposure
• Regulated industries: Healthcare, finance, defense compliance

No Training on Your Code

GitHub states they don't train on private repositories, but public code is fair game. Local AI = your code is never used for training anyone else's model.

Offline Coding

Code on airplanes, in secure facilities, or during internet outages. Once models are downloaded, you're completely independent.

Compliance-Ready

GDPR, HIPAA, SOC 2, ISO 27001 — local AI makes compliance simpler since data never leaves your infrastructure.