<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>开源模型 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E5%BC%80%E6%BA%90%E6%A8%A1%E5%9E%8B/</link><description>Recent content in 开源模型 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 16 Jul 2026 11:07:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E5%BC%80%E6%BA%90%E6%A8%A1%E5%9E%8B/index.xml" rel="self" type="application/rss+xml"/><item><title>开源大模型生态2026：Llama、Qwen、DeepSeek三足鼎立</title><link>https://guijiagi.com/posts/b1-4b9b3771/</link><pubDate>Thu, 16 Jul 2026 11:07:00 +0800</pubDate><guid>https://guijiagi.com/posts/b1-4b9b3771/</guid><description>2026年开源大模型生态格局深度分析，从Llama到Qwen到DeepSeek的技术路线与选型指南</description></item><item><title>开源大模型生态2026：Llama、Qwen、DeepSeek三足鼎立格局分析</title><link>https://guijiagi.com/posts/b2-1ca3f5e0/</link><pubDate>Thu, 16 Jul 2026 10:06:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-1ca3f5e0/</guid><description>深度分析2026年开源大模型生态格局，对比Llama、Qwen、DeepSeek等主流开源模型的技术特征与选型建议</description></item><item><title>开源vs闭源大模型：2026年的格局与趋势</title><link>https://guijiagi.com/posts/article-61/</link><pubDate>Mon, 13 Jul 2026 03:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-61/</guid><description>全面分析2026年开源与闭源大模型的竞争格局，从能力差距、商业模式、生态建设、安全治理多维度对比</description></item><item><title>开源大模型的商业化路径分析</title><link>https://guijiagi.com/posts/article-45/</link><pubDate>Mon, 13 Jul 2026 00:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-45/</guid><description>从Llama到DeepSeek，开源大模型如何找到可持续的商业化模式</description></item><item><title>开源大模型的商业化路径分析</title><link>https://guijiagi.com/posts/b2-85ab788e/</link><pubDate>Mon, 13 Jul 2026 00:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-85ab788e/</guid><description>从Llama到DeepSeek，开源大模型如何找到可持续的商业化模式</description></item><item><title>2026年开源大模型排行榜：谁在挑战GPT-5</title><link>https://guijiagi.com/posts/article-03/</link><pubDate>Sun, 12 Jul 2026 17:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/article-03/</guid><description>全面盘点2026年上半年开源大模型格局，从Llama 4到Qwen 3，分析谁有实力挑战闭源巨头</description></item><item><title>2026年开源大模型排行榜：谁在挑战GPT-5</title><link>https://guijiagi.com/posts/b2-6309acce/</link><pubDate>Sun, 12 Jul 2026 17:20:00 +0800</pubDate><guid>https://guijiagi.com/posts/b2-6309acce/</guid><description>全面盘点2026年上半年开源大模型格局，从Llama 4到Qwen 3，分析谁有实力挑战闭源巨头</description></item><item><title>Nous Hermes 4架构解析：开源函数调用模型的新标杆</title><link>https://guijiagi.com/posts/nous-hermes4-architecture/</link><pubDate>Wed, 08 Jul 2026 11:30:00 +0800</pubDate><guid>https://guijiagi.com/posts/nous-hermes4-architecture/</guid><description>Nous Hermes 4架构深度解析：函数调用能力、微调方案、与Llama对比及企业应用实践</description></item><item><title>开源vs商业模型2026决策指南</title><link>https://guijiagi.com/posts/open-source-vs-commercial-2026/</link><pubDate>Thu, 02 Jul 2026 10:53:00 +0800</pubDate><guid>https://guijiagi.com/posts/open-source-vs-commercial-2026/</guid><description>2026年开源与商业大模型的全面对比与选型决策框架</description></item><item><title>Mistral Large 3评测：欧洲AI的崛起</title><link>https://guijiagi.com/posts/mistral-large-3-review/</link><pubDate>Thu, 02 Jul 2026 10:22:00 +0800</pubDate><guid>https://guijiagi.com/posts/mistral-large-3-review/</guid><description>Mistral AI发布Large 3模型，欧洲AI力量正在崛起</description></item><item><title>Llama 4开源发布：405B参数MoE架构</title><link>https://guijiagi.com/posts/meta-llama4-release/</link><pubDate>Thu, 02 Jul 2026 10:04:00 +0800</pubDate><guid>https://guijiagi.com/posts/meta-llama4-release/</guid><description>Meta发布Llama 4开源大模型，405B参数MoE架构刷新开源模型性能记录</description></item><item><title>Mistral Large 3 评测：欧洲 AI 的最后希望</title><link>https://guijiagi.com/posts/mistral-large-3-review-european-ai-hope/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/mistral-large-3-review-european-ai-hope/</guid><description>Mistral Large 3深度评测：欧洲旗舰大模型的能力分析与竞争力评估</description></item><item><title>开源大模型 2026 中期排行榜：谁在追赶闭源</title><link>https://guijiagi.com/posts/open-source-llm-leaderboard-2026-midyear/</link><pubDate>Sun, 28 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/open-source-llm-leaderboard-2026-midyear/</guid><description>2026年中期开源大模型综合排行榜，深度分析开源阵营与闭源模型的差距变化</description></item><item><title>Nous Hermes 系列模型全面评测</title><link>https://guijiagi.com/posts/nous-hermes-model-review/</link><pubDate>Fri, 26 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/nous-hermes-model-review/</guid><description>从推理能力、指令遵循、多语言表现等维度，全面评测 NousResearch Hermes 系列开源大模型。</description></item><item><title>Codex OSS 模式深度解析：接入任意开源大模型</title><link>https://guijiagi.com/posts/codex-oss-mode-deep/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/codex-oss-mode-deep/</guid><description>深入解析 Codex OSS 模式的工作原理、本地模型接入方法、性能对比与私有部署方案。</description></item><item><title>Llama 系列模型演进史：从 Llama 1 到 Llama 4</title><link>https://guijiagi.com/posts/llama-model-evolution/</link><pubDate>Wed, 24 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llama-model-evolution/</guid><description>回顾 Meta Llama 系列四代模型的架构演进、许可证变化、社区生态与部署建议。</description></item><item><title>DeepSeek 技术解析：开源大模型的性价比之王</title><link>https://guijiagi.com/posts/deepseek-technical-analysis/</link><pubDate>Wed, 24 Jun 2026 11:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/deepseek-technical-analysis/</guid><description>DeepSeek 系列模型的技术架构、训练方法和工程优化深度分析</description></item></channel></rss>