Developer seeks local LLM for 24GB Mac Mini

The 24GB RAM constraint on Apple Silicon requires careful model selection to balance inference speed and capability for coding tasks.

• –24GB unified memory leaves roughly 16-18GB for model weights, limiting choices to heavily quantized 32B models or less quantized 7B-14B models.
• –Models like Qwen2.5-Coder-14B or DeepSeek-Coder-V2-Lite are likely the sweet spot for this specific hardware footprint.
• –Running models locally for daily development significantly reduces API costs while ensuring code privacy and offline availability.
• –This highlights a growing trend of developers optimizing local LLM setups for specific tech stacks (like Terraform and React) rather than relying solely on cloud providers.