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

Описание и применение

Замена платных AI‑инструментов на бесплатный локальный стек сократила расходы до нуля, улучшила латентность и обеспечила работу без подключения к интернету.

Задача

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

Результат

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

Рабочий процесс

• 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

Доказательства

$0/month vs $45/month

Источник

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

Источник