# What is the best local LLM for coding?

The best local coding LLM depends on your hardware — but Qwen, DeepSeek-Coder, and Llama variants are strong starting points in 2026.

There is no single winner — the best local LLM for coding depends on your GPU/RAM and whether you need autocomplete speed or deep reasoning.

Strong picks in 2026:

Qwen 2.5 Coder — excellent code quality per gigabyte; good on 16 GB machines per Alibaba's Qwen 2.5 Coder release notes.
DeepSeek Coder V2 — strong on harder bugs and refactors if you have VRAM headroom; see DeepSeek's Coder documentation.
Llama 3.x Instruct — solid general coding plus explanation; widely supported in tools via Ollama's Llama builds.
Use Ollama or your IDE's local model integration (Continue documents local endpoints). For daily driver work on a 16 GB laptop, start with a 7B–14B coder model and benchmark on your repo before chasing 70B downloads.



## Sources
1. [Qwen 2.5 Coder — model card (Hugging Face)](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct)
2. [Qwen 2.5 Coder family — release blog](https://qwenlm.github.io/blog/qwen2.5-coder-family/)
3. [DeepSeek Coder V2 Lite — model card](https://huggingface.co/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct)
4. [DeepSeek Coder (GitHub)](https://github.com/deepseek-ai/DeepSeek-Coder)
5. [Meta Llama](https://www.llama.com/)
6. [Ollama — Llama 3.2](https://ollama.com/library/llama3.2)
7. [Continue — local autocomplete models](https://docs.continue.dev/customize/model-types/autocomplete)

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Page: https://localizedaiguide.com/q/best-local-llm-for-coding