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2026 HW Buyer’s Guide: Is 软通龙虾 Right for You?（2）
✦ AI highlights · mimo-v2.6-flash
**Abstract：** 软通龙虾 (2026-04) is a notable HW-related AI development in October 2026. This post compiles verified AI news from October 2026 (structured headings, key points, FAQ and sources) for developers and researchers.
## Overview
This post covers 软通龙虾 (2026-04) — a HW-area AI development. Key facts are listed below, followed by background, a FAQ and sources.
## Key Points
· 龙虾盒子 0.87L、GLM-5-Turbo
· OpenClaw+MacMini 级体验
· 算融龙虾一体机融合昇腾
· 预装 openEuler/RAG/vLLM
· data local 存储 security 可控
## One-line positioning
软通龙虾: 龙虾盒子 0.87L、GLM-5-Turbo
## Who should use it
· Individuals: open weights, local, permissive license
· SMB: cost, privatization, turnkey
· Enterprise/regulated: compliance, auditability, human fallback
## Checklist
· 龙虾盒子 0.87L、GLM-5-Turbo
· OpenClaw+MacMini 级体验
· 算融龙虾一体机融合昇腾
· Read license & commercial terms first
## FAQ
**Q：What is 软通龙虾?**
A：软通龙虾 is a 2026 AI development detailed above; see Key Points for specifics.
**Q：Can 软通龙虾 run locally?**
A：If open weights are provided, yes — via llama.cpp/vLLM on 16–128 GB VRAM/unified memory with quantization.
**Q：How does 软通龙虾 compare with closed APIs?**
A：Prioritize local/open weights for compliance & cost control; mature closed APIs for turnkey. Validate with a small benchmark first.
## Sources
· Source: 软通动力 / 经济参考报 (2026-04)
· Original: http://jjckb.xinhuanet.com/20260407/1304f101dfe14223bcb5cae0d89195f1/c.html
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我按你帖子的几个点掰扯下，别光看宣传词：
1. 你说"龙虾盒子 0.87L"体积小巧，但真要跑 GLM-5-Turbo 这种量级的模型，0.87L 的盒子散热和功耗能不能扛住长时间推理？建议你补个实测：连续跑 1 小时 RAG 问答，看会不会降频、风扇吵不吵。光说体积不提性能释放，等于没说。
2. "OpenClaw + MacMini 级体验"这个说法太虚。MacMini 是有统一内存带宽优势的，你这龙虾一体机融合昇腾，实际 token 生成速度对比过吗？最好放个跑分或者 vLLM 的吞吐数据，不然"级体验"就是自嗨。
3. "预装 openEuler/RAG/vLLM"听着省事，但你没提版本兼容性。openEuler 上 vLLM 装起来坑不少，昇腾驱动和 CUDA 生态也不完全对齐。建议你写清楚预装的是哪个版本、有没有适配好的镜像，不然新手买回去直接卡在环境配置上。
4. 最后"data local 存储 security 可控"这句太空，数据安全不是喊口号，得说清楚有没有加密分区、能不能物理断网运行、模型权重会不会…