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Best IDE Plugins for Local LLMs in 2026 (VS Code & JetBrains)

··By Hans Kuepper · Founder of PromptQuorum, multi-model AI dispatch tool · PromptQuorum
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Continue (VS Code + JetBrains) is the best free IDE plugin for local LLMs in 2026: it connects natively to Ollama and any OpenAI-compatible API, supports chat + autocomplete + context-aware code editing, and runs entirely on your hardware with zero data leaving your machine.

This page contains links to third-party products for reference. PromptQuorum is not enrolled in any affiliate program — these are plain links that earn no commission.

Key Takeaways

  • Continue (open-source) is the default choice: native Ollama support, VS Code + JetBrains
  • Cline agents read/write files and run shell commands — most powerful for agentic tasks
  • Tabby runs its own inference server (1–3B models) — lowest latency autocomplete
  • Aider is the terminal-first option — git-commit-aware, multi-file rewrites
  • Cursor supports local models (Ollama/LM Studio) but its best features require cloud
  • All four work with Ollama; only Tabby requires its own backend server

Best IDE Plugins for Local LLMs — Ranked

📍 In One Sentence

Continue is the best IDE plugin for local LLMs in 2026 because it supports Ollama natively, works in both VS Code and JetBrains, and provides chat, autocomplete, and code editing without any cloud dependency.

💬 In Plain Terms

An IDE plugin for local LLMs connects your code editor (VS Code, IntelliJ) to a model running on your own machine (via Ollama, LM Studio, or llama.cpp). The model sees your code and responds — no code leaves your computer, no API fees, no usage limits.

Quick Setup: Continue + Ollama in VS Code

The fastest way to start local LLM coding:

  1. 1
    Install Ollama: curl -fsSL https://ollama.com/install.sh | sh
  2. 2
    Pull a coding model: ollama pull qwen2.5-coder:14b
  3. 3
    In VS Code, install Continue from the Extensions marketplace
  4. 4
    Open Continue settings (Cmd+Shift+P → "Continue: Open Config")
  5. 5
    Add Ollama provider: set provider: "ollama", model: "qwen2.5-coder:14b"
  6. 6
    Restart VS Code — Continue tab appears in sidebar
  7. 7
    Press Cmd+L to open chat, or start typing and press Tab for autocomplete

Best Local Models by Plugin and Task

Can Continue replace GitHub Copilot entirely for local use?

For most use cases, yes. Continue with Qwen2.5-Coder 14B Q8 provides comparable autocomplete quality to GitHub Copilot for Python, TypeScript, and Go. Copilot still has an edge in very new APIs and obscure library usage where its training data advantage shows. For privacy-critical codebases, Continue + local Ollama is the better choice.

Which plugin works best for multi-file refactoring?

Cline or Aider. Both can read multiple files, understand dependencies, and make coordinated edits across a codebase. Cline works inside VS Code (better for visual feedback); Aider works in the terminal (better for CI/CD integration and git-aware commits). For 30B+ models with 24 GB VRAM, Cline with Qwen2.5-Coder 32B handles complex refactoring reliably.

Does Tabby work without a GPU?

Yes — Tabby can run on CPU with small models (1–3B). However, autocomplete latency on CPU is 500ms–2s, which feels sluggish compared to the <200ms target for smooth coding. For CPU-only machines, Continue + Ollama with a fast 1B or 3B model gives better latency control.

Can I use these plugins with LM Studio instead of Ollama?

Yes. LM Studio exposes an OpenAI-compatible API on port 1234 by default. Set your plugin provider to "openai" with base URL http://localhost:1234/v1 and use any model name from your LM Studio library. Continue, Cline, and Aider all support this configuration.

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