Twinny
Twinny is an AI code completion extension for Visual Studio Code. It operates locally, ensuring your code remains private, and is designed ...
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What is Twinny?
Twinny is a free AI extension for Visual Studio Code that provides AI‑assisted coding features such as real‑time code completion and an integrated chat interface for discussing your code. It supports multiple AI backends including localhost OpenAI/Ollama‑compatible APIs, OpenAI, Anthropic, OpenRouter, Deepseek, Cohere, Mistral AI, Perplexity, and Groq, so you can run the model locally or connect to cloud providers. The extension focuses on privacy and flexibility, allowing offline operation and self‑hosted AI setups while still offering the convenience of cloud‑based inference when needed.
Key capabilities include fill‑in‑the‑middle code completion, where Twinny suggests snippets in the middle of lines or blocks of code, and a sidebar chat that lets you ask for explanations, generate tests, refactor code, and more. It also offers Git commit message generation, configurable prompt templates, and a side‑by‑side diff view so you can compare AI‑suggested changes against your original code. The extension preserves chat conversations, supports single and multiline completions, and lets you accept code solutions directly into your editor or create new documents from returned code blocks.
Twinny is aimed at developers who want a GitHub Copilot‑style experience but with more control over where the AI runs and how their code is handled. It is especially useful for those who prefer local or private AI hosting, want to avoid vendor lock‑in, and need a lightweight, customizable assistant inside VS Code. The added workspace embeddings and Symmetry network integration further tailor suggestions to your project context and let you share AI inference resources in a peer‑to‑peer fashion, making it attractive for teams or individuals experimenting with decentralized AI workflows.
Twinny pricing
Pricing model: Free
Twinny is free to use and does not charge for the extension or core features; it is distributed as open‑source software under the MIT license. There is no paid tier bundled with the extension itself, but users who connect to cloud AI providers may incur costs from those providers' API usage or subscriptions. The project accepts voluntary donations via Bitcoin and other channels for those who wish to support ongoing development.
Twinny pros
- Free to use with no subscription required
- Runs fully offline when connected to a local model
- Supports multiple AI providers including OpenAI, Anthropic, and many others
- Locally hosted or self‑hosted backend option for privacy
- Fill‑in‑the‑middle code completion for natural inline suggestions
- Sidebar chat for explanations, tests, and refactoring guides
- Chat conversations are preserved between sessions
- Configurable API endpoints and model selection
- OpenAI‑API‑standard‑compliant backend interface
- Single and multiline completion suggestions
- Customizable prompt templates for tailored responses
- Git commit message generation directly from the extension
- Easy installation via the VS Code marketplace
- Workspace embeddings for context‑aware suggestions
- Symmetry network integration for P2P AI inference sharing
- Direct code acceptance into the editor from AI responses
- New document creation from AI‑generated code blocks
- Side‑by‑side diff view for comparing AI suggestions with original code
- Full‑screen chat mode for focused interaction
- Code solution block copying for quick reuse
Twinny cons
- No built‑in free cloud tier; requires setting up your own API or local model
- Setup complexity when configuring custom backends or local models
- Limited official quality assurance since it is actively developed and provided as is
- Some advanced features depend on external providers' availability and limits
- Symmetry network is still experimental and may be unstable
- Documentation is relatively minimal compared with major commercial tools
- No official mobile or web IDE support, only VS Code
- Advanced configuration may require technical familiarity with AI APIs and networking
Frequently asked questions about Twinny
What is Twinny and what does it do?
Twinny is a free AI extension for Visual Studio Code that adds AI‑assisted code completion and chat directly inside the editor. It can suggest code as you type, explain your existing code, generate tests, propose refactoring, and even help with Git commit messages, all powered by configurable AI backends that you can run locally or remotely.
Can I run Twinny completely offline?
Yes; Twinny supports offline operation when you connect it to a local OpenAI‑compatible API server or a compatible model such as Ollama running on your machine. In this mode no code is sent to external cloud providers, which strengthens privacy and reduces dependency on internet connectivity.
Which AI models and providers does Twinny support?
Twinny supports a wide range of providers and backends, including local OpenAI‑compatible APIs, OpenAI, Anthropic, OpenRouter, Deepseek, Cohere, Mistral AI, Perplexity, and Groq. You can configure which provider and model to use in the extension settings so you can switch between cloud and self‑hosted options as needed.
How does the fill‑in‑the‑middle code completion work?
Fill‑in‑the‑middle completion lets Twinny suggest code snippets that fit inside existing lines or blocks, not just at the end of a line. This makes it feel more natural when you are writing expressions, conditionals, or function calls, and you can accept multiple suggestions inline without having to restructure the surrounding code manually.
What is the chat interface for?
The chat interface lets you describe parts of your codebase, ask for explanations, request test cases, suggest refactoring, or even get help designing new features. Conversations are preserved so you can return to earlier discussions, and you can apply generated code blocks directly into your files or create new documents from them.
How does Twinny handle privacy and code security?
Twinny is designed to be privacy‑focused: you control whether code is sent off‑device by choosing local or remote backends. When using a local model or self‑hosted API, your code never leaves your machine, while cloud‑based providers only see what you choose to send through their APIs, subject to their own terms and privacy policies.
What are workspace embeddings and how do they help?
Workspace embeddings let Twinny build a contextual understanding of your project by indexing your codebase, so suggestions and chat responses become more relevant to your specific files, patterns, and dependencies. This means the assistant can reason about your project as a whole rather than only the current file or snippet.
What is the Symmetry network and why would I use it?
The Symmetry network is a peer‑to‑peer layer that allows Twinny users to share AI inference resources, such as compute nodes or model instances, across a decentralized network. This can help lower costs or speed up inference by leveraging distributed hardware instead of relying solely on a single local or cloud backend.
Is Twinny open‑source and can I contribute?
Yes, Twinny is open‑source under the MIT license and the project welcomes contributions. Developers can propose changes via GitHub issues, submit pull requests, and collaborate with the maintainers, using channels like Twitter to coordinate larger feature work or bug fixes.
Are there any limitations to using Twinny compared with commercial tools like Copilot?
Because Twinny is community‑driven and free, it may lag behind commercial tools in polish, documentation, and out‑of‑the‑box setup, and some advanced tooling integrations may require manual configuration. However, it compensates by offering more deployment flexibility, local operation, and openness to custom backends and networks.