Best Local AI Models for Coding
Running a coding assistant locally gives you zero-latency completions, full privacy for proprietary code, and no API costs. The best coding models for local use combine strong code generation with fast inference on Apple Silicon. Here are the top picks across all hardware configurations.
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Top Coding Models (All Hardware)
RAM Requirements
min 24 GB
min 192 GB
min 48 GB
min 24 GB
min 24 GB
min 80 GB
min 256 GB
min 256 GB
Frequently Asked Questions
What is the best local AI model for coding?
For most developers, Qwen3.5 9B offers the best balance of code quality and speed on 16GB RAM. If you have 32GB+, Qwen3 14B or the Qwen3.6 MoE models deliver noticeably stronger code generation and review.
Can I use a local AI model as a coding copilot?
Yes. Tools like Continue.dev, Cline, and aider support Ollama as a backend. Run any coding model locally and connect it to your IDE for completions, chat, and code review without sending code to the cloud.
How much RAM do I need for a coding AI model?
A capable coding model needs at least 10GB RAM (7B-9B Q4 models). For professional-grade code assistance with 14B+ models, plan for 16-24GB. The sweet spot for most developers is a 9B-14B model on 16-32GB RAM.
Are dedicated coder models better than general models for coding?
Less than they used to be. Current general models like Qwen3.5 9B match or beat older dedicated coder models (Qwen2.5 Coder, Codestral) on most tasks. Dedicated coders still help for fill-in-the-middle autocomplete.