阿里巴巴的Qwen 3.8大语言模型

Qwen 3.8是阿里巴巴云开发的一个拥有2.4T参数的大语言模型，旨在在AI模型市场中竞争。 该项目因其846个星标和Hacker News上的活跃讨论而具有重要意义，表明了强烈的社区兴趣。它通过代币计划具有潜在的盈利能力，将其定位为LLM领域的一个有竞争力的参与者。 该模型通过代币计划提供访问权限，表明了商业焦点。它目前处于生产成熟度。

项目链接：https://twitter.com/Alibaba_Qwen/status/2078759124914098291 作者：nh43215rgb 发布时间：2026-07-19T08:44:57Z 挖掘日期：2026-07-20 AI 评分：9.0/10 来源：hackernews 标签：LLM, AI, Alibaba, Cloud, NLP

📌 项目详解

Qwen 3.8是阿里巴巴云开发的一个拥有2.4T参数的大语言模型，旨在在AI模型市场中竞争。 该项目因其846个星标和Hacker News上的活跃讨论而具有重要意义，表明了强烈的社区兴趣。它通过代币计划具有潜在的盈利能力，将其定位为LLM领域的一个有竞争力的参与者。 该模型通过代币计划提供访问权限，表明了商业焦点。它目前处于生产成熟度。

🌐 背景与生态

大语言模型（LLMs）是AI领域快速发展的一个领域，主要科技公司正在竞争发布更强大和开放权重的模型。Qwen 3.8在Moonshot AI的Kimi K3等类似模型宣布后进入这个竞争格局。

💬 社区讨论

社区评论表达了混合情绪，有些人对开放权重的潜力感到兴奋，其他人则批评Qwen 3.7 Pro的可用性和成本。人们期待开放权重的发布。

🚀 应用前景

Qwen 3.8可以应用于客户服务、内容创作和教育等各个行业。其通过代币计划潜在的盈利能力可能使其对SaaS解决方案和API集成具有吸引力。

🔧 技术栈

Qwen 3.8基于大规模神经网络架构，可能使用PyTorch或TensorFlow等框架，并设计用于处理广泛的自然语言处理任务。

🎯 上手难度

使用Qwen 3.8的难度评级为进阶。前提条件包括兼容的Python版本和访问代币计划。基本步骤包括设置环境和使用提供的API。

👥 目标用户

目标用户包括AI开发者、数据科学家和寻求高级NLP功能的企业。它特别适用于科技和医疗保健行业的用户。

⚖️ 类似项目对比

竞争对手包括OpenAI的GPT-4、Google的BERT和Anthropic的Claude。Qwen 3.8以其对开放权重的关注和具有竞争力的定价而区别于其他模型。

📚 参考链接

• Large language model - Wikipedia

• [AI Demystified: Introduction to large language models

  University IT](https://uit.stanford.edu/service/techtraining/ai-demystified/llm)

• [What Are Large Language Models (LLMs)?

  IBM](https://www.ibm.com/think/topics/large-language-models)

📄 查看原文内容

https://www.qwencloud.com/pricing/token-plan --- Top Comments --- [simonw]: (I can't draw a pelican for this one because Alibaba Cloud have flagged my email address and won't let me pay them for access. So I'm waiting for the open weights release, or for the new model to show up on OpenRouter.) [adrian_b]: I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to better compete with Moonshot AI. In any case, from this competition in LLMs, we win. [5701652400]: in my experience of 1 month daily use, Qwen 3.7 Pro is just unusable. wastes too much time, goes off track, useless stuck loops, cannot debug at all. Deepseek V4 Pro is night-and-day compare to Qwen. actually Qwen models seems the worst SWE experience so far. and it is super expensive compare to Deepseek. cannot delegate anything to it, cannot use it real-time low-level tasks either. totally unusable. [vitorgrs]: Deepseek 4 "final" version is imminent as well. Will probably be at Opus 4.8 level, and I find it pretty big deal because of Deepseek price... [overgard]: I've been using Qwen 3.6 27B with LMStudio, and I was pleasantly surprised with it, although it was a little slow. I found mtplx last night, and it really wasn't an exaggeration to say that it ran the model 2-3x faster which was super impressive. I'm trying to move to local models as much as I can, and I'm finding that it's becoming more and more practical. Admittedly this is on a $6000 dollar laptop (M5 Max Macbook with the specs maxxed out), so the hardware is still...