I Replaced Cursor, Copilot, and Windsurf with a $0 Local Stack — 60 Days Later I'm Not Going Back

说明与用途

用免费本地 AI 堆栈替代付费工具，成本降至零，延迟提升，支持离线使用。

问题

High monthly costs for AI coding assistants with limited offline use and data privacy concerns.

结果

Reduced monthly cost from $45 to $0, improved latency (~180ms vs ~300ms), offline usage, and maintained 95% of autocomplete quality.

工作流

• 1. Install Ollama and pull qwen2.5-coder:7b
• 2. Install Continue.dev VS Code extension
• 3. Configure Continue.dev to use local Qwen model
• 4. Set up Tabby as a self-hosted completion server
• 5. Use MonkeyCode for multi-file agent tasks
• 6. Run Ollama with keep-alive to avoid cold-start latency

证据

$0/month vs $45/month

来源

~180ms (local, no network) vs ~300ms

来源