Best Local LLM for Coding: 8GB to 24GB VRAM Picks

Описание и применение

Пошаговый рецепт выбора и запуска локальной модели LLM для кода, учитывая VRAM GPU, с помощью Ollama.

Задача

Developers need a fast, offline coding assistant that fits their GPU VRAM constraints.

Результат

Users can run a local coding LLM that matches their GPU VRAM, achieving fast autocomplete and refactor capabilities without external API costs.

Рабочий процесс

• 1. Determine GPU VRAM and choose model from table
• 2. Install Ollama (Linux) with curl script
• 3. Pull the selected model with ollama pull
• 4. Run interactively with ollama run or expose API via curl
• 5. Export OPENAI_BASE_URL for tools that expect it

Доказательства

The best local LLM for coding right now is Qwen3 Coder 30B A3B on a 24 GB card, Qwen2.5 Coder 14B at Q4 on 12–16 GB, and Qwen2.5 Coder 7B at Q4 on 8 GB.

Источник

Five commands, from nothing to an OpenAI-compatible API your editor can use: ...

Источник