微型（≤1B，内存≤1GB）

• TinyLlama‑1.1B‑Chat（INT4）：约0.6GB，内存≥1GB；GPT4All 内置一键下载
• GPT4All‑Mini（350M，INT4）：约0.2GB，内存≥512MB；https://gpt4all.io/models/gpt4all‑mini‑lm‑lora‑new‑bpe.gguf

轻量（7B，内存≥4GB）

• Llama 2‑7B‑Chat（Q4_K_M）：约3.8GB，内存≥4GB；https://gpt4all.io/models/llama‑2‑7b‑chat.Q4_K_M.gguf
• Mistral‑7B‑Instruct（Q4_0）：约3.8GB，内存≥4GB；https://gpt4all.io/models/mistral‑7b‑instruct‑v0.2.Q4_0.gguf
• Orca 2‑7B（Q4_0）：约3.8GB，内存≥4GB；https://gpt4all.io/models/orca‑2‑7b.Q4_0.gguf
• MPT‑7B‑Instruct（Q4_0）：约3.8GB，内存≥4GB；https://gpt4all.io/models/mpt‑7b‑instruct.Q4_0.gguf

中大型（13B，内存≥8GB）

• Llama 2‑13B‑Chat（Q4_K_M）：约6.8GB，内存≥8GB；https://gpt4all.io/models/llama‑2‑13b‑chat.Q4_K_M.gguf
• WizardLM‑13B‑v1.2（Q4_0）：约6.8GB，内存≥8GB；https://gpt4all.io/models/wizardlm‑13b‑v1.2.Q4_0.gguf

专业编码（商用优先）

• StarCoder‑7B（Q4_0）：约3.8GB，内存≥4GB；https://gpt4all.io/models/starcoder‑7b.Q4_0.gguf
• CodeLlama‑7B‑Instruct（Q4_0）：约3.8GB，内存≥4GB；https://gpt4all.io/models/codellama‑7b‑instruct.Q4_0.gguf

Win7 要点

• 模型选INT4 量化，优先 **≤3.8GB**，搭配 GPT4All 3.9.0+ 64 位更稳
• 文档量大时，用 LocalDocs+TinyLlama，检索更流畅

阿雪技术观

在科技发展浪潮中，我们不妨积极投身技术共享。不满足于做受益者，更要主动担当贡献者。无论是分享代码、撰写技术博客，还是参与开源项目维护改进，每一个微小举动都可能蕴含推动技术进步的巨大能量。东方仙盟是汇聚力量的天地，我们携手在此探索硅基生命，为科技进步添砖加瓦。

Hey folks, in this wild tech - driven world, why not dive headfirst into the whole tech - sharing scene? Don't just be the one reaping all the benefits; step up and be a contributor too. Whether you're tossing out your code snippets, hammering out some tech blogs, or getting your hands dirty with maintaining and sprucing up open - source projects, every little thing you do might just end up being a massive force that pushes tech forward. And guess what? The Eastern FairyAlliance is this awesome place where we all come together. We're gonna team up and explore the whole silicon - based life thing, and in the process, we'll be fueling the growth of technology.