什么是 LM Studio？

Gemma 4 12B is a unified, encoder-free multimodal model bringing high-performance multimodal intelligence to your laptop. It matches the performance of our 26B MoE at less than half the memory footprint, supports native audio inputs, and runs locally on 16GB VRAM hardware with low-latency multi-step reasoning.

本地AI模型在编码场景中具备可行性，但受硬件资源和工具链限制，需权衡模型规模与性能表现。

Ornith-1.0是DeepReinforce发布的开源大模型，基于Gemma和Qwen，支持多种参数规模，在编码任务中表现优异。

未来AI将主导多数任务，但六项核心技能仍具价值，包括管理AI代理、本地模型运行等。

本地模型在2026年已足够强大，可替代Claude Code完成代码相关任务，无需依赖第三方API。

本地运行大语言模型（LLMs）可通过 llama.cpp、Ollama 和 LM Studio 等工具实现，兼顾隐私与学习。

Zed now supports direct use of local AI models like Gemma-4 12B and Qwen-3.6 in the editor, enhancing privacy and experimentation efficiency.

Running Qwen 3.5-9B (q4_k_s quantized) on an M4 MacBook with 24GB RAM achieves ~40 tokens/sec, supports 128K context and tool use for local development.