Want to keep code on your machine or private network while using Ollama, local models, or a private model service? Compare different leading tools for individual development, automation, team deployment, and Git or terminal workflows.
Its autonomy requires reviewing proposed commands and file changes.
Agent permissions and model configuration affect results; review commands and file changes before applying them.
It requires more infrastructure and operations than a single-user plugin.
There is no IDE-plugin UI, so graphical-editor users may need to adapt to the terminal.
Continue was acquired by Cursor, and its official repository is now read-only and no longer actively maintained. The open-source code remains available for evaluating existing deployments, migrations, or follow-on development; new projects should prioritize actively maintained alternatives.
| Tool | How you use it | Setup effort | Ollama / local model connection | Good for |
|---|---|---|---|---|
| Cline | IDE agent plugin | ⚡ Low (model setup required) | ✅ Configurable connection | Tasks that inspect projects, edit multiple files, and run commands |
| Roo Code | IDE multi-mode agent plugin | ⚡ Low (model setup required) | ✅ Configurable connection | Developers who want to switch between agent, architecture, and Q&A modes |
| Tabby | Team self-hosted service | 🔧 Moderate (server required) | ➖ Run the model and service on a server | Team-wide deployment on company servers or private networks |
| Aider | CLI / Git assistant | ⚡ Low (model setup required) | ✅ Configurable connection | Coding workflows centered on the terminal and Git |
| Continue | IDE coding assistant (archived) | ⚡ Low (model setup required) | ✅ Configurable connection (OSS edition) | Evaluating existing deployments or building on the open-source codebase |
It depends on the model, context length, and whether you use a GPU. Smaller models can often run on a typical development machine, while larger models need more system memory and, for GPU inference, enough VRAM. Your editor, code index, and model share those resources. Check the model's requirements first, then test speed and quality on a small project.
There is no single answer for every tool. Continue, Cline, Roo Code, and Aider can be configured to use local or compatible API services, while Tabby is more commonly run as a server that provides the model service to IDE integrations. Support for a particular Ollama model, API format, or feature depends on the tool and its current configuration. Check the project's latest documentation before setting it up.
Not by itself. Check the editor extension or frontend's API endpoint, telemetry, sign-in services, model downloads, and extensions in addition to the model. A meaningful data boundary exists only when code requests go to infrastructure you control and no additional reporting is enabled. Review the project's privacy information and, where possible, inspect network requests.
Start with the workflow rather than the word “local.” Evaluate Continue for editor completion and Q&A; compare Roo Code and Cline for agent-style tasks and multi-file work; consider Aider for terminal- and Git-centered workflows; and look at Tabby when a team wants a centrally managed model service and access layer. Then compare model hosting, permissions, code privacy, and maintenance effort.
Running locally usually means the model or tool runs directly on your computer. It suits individual use but depends on your hardware and maintenance. Self-hosting means deploying a service on infrastructure you control, such as a server, cloud environment, or private network, which can support shared access and centralized management. Neither term automatically means fully offline or zero data sharing; verify API endpoints, telemetry, sign-in services, and data storage.
