Key Takeaways
- Continue.dev acquired by Cursor (June 2026) — v2.0.0 is the final release, repo read-only; still runs with Ollama but no longer maintained
- Cline is now the best maintained free BYOK alternative: VS Code + JetBrains, agentic file editing, MCP tools, 5M+ installs
- Tabby runs its own inference server (1–3B models) — lowest latency autocomplete for teams
- Aider is the terminal-first option — git-commit-aware, multi-file rewrites, 44K GitHub stars
- Cursor ($20/month Pro, credit-based) acquired both Supermaven and Continue.dev; SpaceX agreed to acquire Cursor for $60B in June 2026
- All tools 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:
- 1Install Ollama:
curl -fsSL https://ollama.com/install.sh | sh - 2Pull a coding model:
ollama pull qwen2.5-coder:14b - 3In VS Code, install Continue from the Extensions marketplace
- 4Open Continue settings (Cmd+Shift+P → "Continue: Open Config")
- 5Add Ollama provider: set
provider: "ollama",model: "qwen2.5-coder:14b" - 6Restart VS Code — Continue tab appears in sidebar
- 7Press Cmd+L to open chat, or start typing and press Tab for autocomplete
Best Local Models by Plugin and Task
| Plugin | Best Coding Model (Local) | Best Chat Model (Local) | Min VRAM |
|---|---|---|---|
| Continue | Qwen3-Coder 14B Q8 | Llama 3.3 8B Q4 | 16 GB |
| Cline | Qwen3-Coder 32B Q4 | Qwen3 32B Q4 | 24 GB |
| Tabby | StarCoder2-7B (built-in) | N/A (code only) | 8 GB |
| Aider | Qwen3-Coder 14B (editor) | Qwen3-Coder 32B (architect) | 16–24 GB |
| Cursor | DeepSeek-Coder-V2 (via Ollama) | Qwen3 14B | 16 GB |
Can Continue replace GitHub Copilot entirely for local use?
As of June 2026, Continue has been acquired by Cursor and v2.0.0 is the final release (repo is read-only). The extension still runs with Ollama and BYO-LLM, but receives no further development from the original team. For a maintained open-source alternative, Cline is the recommended replacement — it offers the same BYOK model, works in VS Code and JetBrains, and adds agentic file editing. GitHub Copilot Pro costs $10/month with $15/month in AI credits; Cline is free with your own API key.
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 Qwen3-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.