Cline vs Continue: Which AI Tool Is Right for Your Hardware?
Side-by-side comparison of local model support, GPU requirements, OpenRouter compatibility, pricing, and setup difficulty. Find which tool fits your workflow and hardware.
Cline
Open-source AI coding agent for VS Code. Autonomously explores your codebase, edits files, runs terminal commands, and uses browser automation.
Continue
Open-source AI code assistant for VS Code and JetBrains. Tab autocomplete, chat, and agent mode with separate models per role — like a local Copilot.
Feature comparison
| Feature | Cline | Continue |
|---|---|---|
| Type | coding agent | coding agent, developer tool |
| Open source | Yes | Yes |
| Pricing | open-source | open-source |
| Platforms | vscode, cli | vscode, jetbrains |
| Local models | Yes | Yes |
| OpenRouter | Yes | Yes |
| Ollama | Yes | Yes |
| GPU needed | Yes | No |
| CPU-only | No | Yes |
| Setup | medium | medium |
Which should you choose?
Choose Cline if
- Autonomous multi-file coding with cloud models
- Codebase exploration and refactoring
- OpenRouter-powered budget coding with DeepSeek
Choose Continue if
- Copilot-like autocomplete with local models for privacy
- Multi-model workflows (local autocomplete + cloud agent)
- Teams wanting IDE integration without vendor lock-in
Hardware requirements
Cline
24 GB VRAM recommended for local coding models. 12 GB is NOT sufficient for serious agentic coding — Cline's ~15K token system prompt alone consumes significant context. 16 GB is borderline for 14B models at Q4 with short context.
Continue
8 GB VRAM for 7B autocomplete/chat models. 16 GB for 14B agent mode. Agent mode with local models requires explicit tool_use capability config.
Full compatibility details
Frequently asked questions
- Which is better for local models: Cline or Continue?
- Both Cline and Continue support local models via Ollama. The choice depends on your specific workflow and hardware.
- Do I need a GPU for Cline vs Continue?
- Cline: 24 GB VRAM recommended for local coding models. 12 GB is NOT sufficient for serious agentic coding — Cline's ~15K token system prompt alone consumes significant context. 16 GB is borderline for 14B models at Q4 with short context. Continue: 8 GB VRAM for 7B autocomplete/chat models. 16 GB for 14B agent mode. Agent mode with local models requires explicit tool_use capability config.
- Which is cheaper: Cline or Continue?
- Both Cline (open-source) and Continue (open-source) have comparable pricing models.