Unsloth 发布 Qwen3.8-27B 的 GGUF 量化版本，17GB 内存可本地运行
Qwen3.8-27B can now be run locally! ✨
Unsloth 宣布 Qwen3.8-27B 现已可通过其 Dynamic GGUF 在本地运行，17GB 内存即可跑起来，同时上传了 NVFP4 量化版本，并附上 GGUF 下载链接与使用指南。被引用的 Qwen 官方推文介绍，Qwen3.8-27B 是原生多模态稠密模型，27B 参数下整体表现超过 Qwen3.7-Plus，在真实编码与办公工作流中表现突出，原生上下文 262K，可通过 YaRN 扩展至 1M tokens，采用 Apache 2.0 许可；Qwen3.8-2.4T-A95B（Max 级）的开放权重也已发布。
推荐理由
AI 评分 57
Unsloth 放出 Qwen3.8-27B 的 GGUF 量化版本，读者可据此判断本地部署的显存门槛与可用性。
主题
查看原帖We promised open weights for Qwen3.8. Now, time to meet them! 🎉 ⚡ Qwen3.8-27B: - A native multimodal dense model. With just 27B parameters, it outperforms Qwen3.7-Plus overall and shines in real-world coding & office workflows. - 262K native context, easily extendable to 1M tokens via YaRN. - Built for builders. Highly efficient, high-quality, and…
展开完整原文
We promised open weights for Qwen3.8. Now, time to meet them! 🎉 ⚡ Qwen3.8-27B: - A native multimodal dense model. With just 27B parameters, it outperforms Qwen3.7-Plus overall and shines in real-world coding & office workflows. - 262K native context, easily extendable to 1M tokens via YaRN. - Built for builders. Highly efficient, high-quality, and licensed under Apache 2.0. 🚀 The open weights for Qwen3.8-2.4T-A95B (Max-level) have also been released recently. Whether you're shipping lightweight applications with Qwen3.8-27B locally or building agents with Qwen3.8-2.4T-A95B, they're yours now! Download, deploy, and build something we haven't imagined yet. 👀👇 - Hugging Face： https://t.co/4kaAcqYEVj - ModelScope： https://t.co/eRIMZCGkhC
正文
当前显示原文，中文全文译文尚未就绪。
Qwen3.8-27B can now be run locally! ✨
Run on 17GB RAM via Unsloth Dynamic GGUFs.
Qwen3.8-27B is by far the strongest model for its size. We also uploaded NVFP4 quants.