{
  "schema_version": "2.1",
  "as_of_date": "2026-10-26",
  "episode": {
    "bvid": "BV1FbnS6FE3e",
    "url": "https://www.bilibili.com/video/BV1FbnS6FE3e/",
    "published_date": "2026-10-25",
    "published_at": "2026-10-25T22:05:16+08:00",
    "title": "盘点一周AI大事(10月25日)｜12G显存跑满血DeepSeek",
    "coverage": {
      "status": "author_summary_aligned",
      "summary_item_count": 19,
      "description_item_count": 11,
      "added_from_summary_count": 8,
      "author_identity_checked": true,
      "summary_transcription_reviewed": true,
      "video_crosscheck_complete": false,
      "note": "19 条已逐条对齐作者评论总结图；不将简介读取完成视为整期完整，尚未逐条核对视频。"
    },
    "summary_image": {
      "local_url": "./assets/2026-10-25-summary.png",
      "label": "产品君本期内容总结图",
      "source": "user_provided_author_summary",
      "author_uid": "1845434732",
      "comment_id": "321871171184",
      "comment_url": "https://www.bilibili.com/video/BV1FbnS6FE3e/?comment_on=1&comment_root_id=321871171184",
      "original_image_url": "https://i0.hdslb.com/bfs/new_dyn/3f52f455c3535746d6d5ecef49535ad61845434732.png",
      "author_comment_verified": true
    }
  },
  "events": [
    {
      "id": "2026-10-25-kimi-k3-1-pro",
      "entity_name": "Kimi K3.1 Pro",
      "entity_type": "model",
      "organization": "Moonshot AI（月之暗面）",
      "original_claim": "月之暗面发布最强开源大模型「Kimi K3.1 Pro」",
      "normalized_summary": "月之暗面发布 Kimi K3.1 Pro，并已在 Kimi 产品与 API 提供；官方计划于 2026 年 11 月 4 日前发布完整模型权重。",
      "availability": "已发布；Kimi 网页、移动端、Work、Code 与 API 可用，具体权限依渠道和套餐而定。",
      "code_license": "未核实",
      "weights_status": "announced_not_released",
      "verification_status": "partially_verified",
      "caveats": [
        "截至 2026-10-25，官方明确完整模型权重尚待发布，不能标为已可下载。",
        "“最强”不是本记录独立验证的事实；官方指标属于发布方报告。",
        "开放权重与开源代码、许可证开放程度需分别记录。"
      ],
      "sources": [
        {
          "kind": "official_announcement",
          "url": "https://www.kimi.com/en/blog/kimi-k3-1-pro",
          "label": "Kimi K3.1 Pro 官方技术博客"
        },
        {
          "kind": "official_docs",
          "url": "https://www.kimi.com/code/docs/kimi-code/whats-new.html",
          "label": "Kimi Code 官方上线记录"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "通用大模型",
        "use_cases": [
          "文本生成",
          "编程"
        ],
        "technical_tags": [],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 1,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://www.kimi.ai/blog/kimi-k3-1-pro"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-claude-duet",
      "entity_name": "Claude Duet",
      "entity_type": "application",
      "organization": "Anthropic",
      "original_claim": "Anthropic推出常驻AI助理「Claude Duet」",
      "normalized_summary": "Anthropic 于 2026 年 10 月 21 日推出 Claude Duet 研究预览，可在云端持续处理任务并主动提示需要关注的信息。",
      "availability": "研究预览；首批面向美国 Pro 和 Max 用户，通过候补名单开放。",
      "code_license": "未见公开代码许可证",
      "weights_status": "not_applicable",
      "verification_status": "verified",
      "caveats": [
        "属于基于 Claude 的 Agent 应用，不是本次发布的新基础模型。",
        "不能将研究预览和候补名单标记为全球全面开放。"
      ],
      "sources": [
        {
          "kind": "official_announcement",
          "url": "https://claude.com/resources/articles/claude-duet",
          "label": "Anthropic：Introducing Claude Duet"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "应用与智能体",
        "subtype": "个人助理",
        "use_cases": [
          "个人助理",
          "办公自动化"
        ],
        "technical_tags": [],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 2,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://claude.com/resources/articles/claude-duet"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-strata",
      "entity_name": "Strata",
      "entity_type": "framework",
      "organization": "Niko1221 / Strata contributors",
      "original_claim": "研究员开源本地部署框架「Strata」，12G显存就能跑满血DeepSeek",
      "normalized_summary": "Strata 是 MIT 许可的本地推理框架；发布记录确认可用单张 12GB 显卡、46–64GB RAM 和 SSD 运行 DeepSeek V4.1-Flash 的低比特量化版本。",
      "availability": "代码及安装包公开；具体支持的硬件、平台和版本见项目文档。",
      "code_license": "MIT",
      "weights_status": "not_applicable",
      "verification_status": "partially_verified",
      "caveats": [
        "“12G”仅指显存；相关配置仍需 46–64GB 系统内存和充足 SSD 空间。",
        "所列模型采用 1.75、2.00 或 2.25 bit 量化，下载约 239–274GB；不是原始精度权重全驻留显存。",
        "“满血”不是明确技术规格，应分别记录模型版本、量化方式、硬件和实测速度。",
        "框架代码许可证不代表其运行的第三方模型权重许可证。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/Niko1221/Strata",
          "label": "Strata 官方 GitHub 仓库"
        },
        {
          "kind": "release_notes",
          "url": "https://github.com/Niko1221/Strata/releases",
          "label": "Strata 发布记录与硬件要求"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "开发工具与基础设施",
        "subtype": "推理部署框架",
        "use_cases": [
          "本地部署",
          "推理优化"
        ],
        "technical_tags": [
          "低比特量化",
          "内存与SSD卸载"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 3,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://github.com/Niko1221/Strata"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-mercury-3",
      "entity_name": "Mercury 3",
      "entity_type": "model",
      "organization": "Inception",
      "original_claim": "Inception推出扩散语言模型「Mercury 3」",
      "normalized_summary": "Inception 于 2026 年 10 月 19 日发布扩散语言模型 Mercury 3，并通过 API 及合作平台提供使用。",
      "availability": "商业网页与 API 可用；官方列出 Inception、OpenRouter、Baseten 和 Vercel 等渠道。",
      "code_license": "未见公开代码许可证",
      "weights_status": "not_verified_public",
      "verification_status": "verified",
      "caveats": [
        "本次核实的官方发布页未声明公开模型权重，不能归入已开源权重模型。",
        "性能和速度数字如后续收录，应标注发布方测试条件。"
      ],
      "sources": [
        {
          "kind": "official_announcement",
          "url": "https://www.inceptionlabs.ai/blog/introducing-mercury-3",
          "label": "Inception：Introducing Mercury 3"
        },
        {
          "kind": "official_docs",
          "url": "https://docs.inceptionlabs.ai/",
          "label": "Inception API 文档"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "通用语言模型",
        "use_cases": [
          "文本生成"
        ],
        "technical_tags": [
          "扩散语言建模"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 4,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://www.inceptionlabs.ai/blog/introducing-mercury-3"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-ai-scientist-v3",
      "entity_name": "AI Scientist v3 / The Agentic Scientist",
      "entity_type": "framework",
      "organization": "Sakana AI",
      "original_claim": "Sakana开源第三代AI科学家「AI Scientist v3」",
      "normalized_summary": "Sakana AI 公开 AI-Scientist-v3 仓库，正式项目名为 The Agentic Scientist，以编程智能体编排构想、实验、评估、消融和论文生成。",
      "availability": "开源代码可获取并自行部署；运行需要所选智能体服务或模型访问权限。",
      "code_license": "Apache-2.0",
      "weights_status": "not_applicable",
      "verification_status": "verified",
      "caveats": [
        "属于科研 Agent 工作流框架，不是单独训练的新基础模型。",
        "开源框架不表示所调用的商业模型免费或开放权重。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/SakanaAI/AI-Scientist-v3",
          "label": "Sakana AI 官方 AI-Scientist-v3 仓库"
        },
        {
          "kind": "official_docs",
          "url": "https://github.com/SakanaAI/AI-Scientist-v3/blob/main/docs/usage.md",
          "label": "The Agentic Scientist 使用文档"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "开发工具与基础设施",
        "subtype": "科研Agent框架",
        "use_cases": [
          "科学研究",
          "自动实验"
        ],
        "technical_tags": [
          "智能体工作流"
        ],
        "basis": "editorial_classification_v2",
        "note": "以开源科研工作流框架的形态交付；在用途主题中归入科学研究与自动实验。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 5,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://github.com/SakanaAI/AI-Scientist-v3"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-harness2",
      "entity_name": "Harness²",
      "entity_type": "framework",
      "organization": "Google Research",
      "original_claim": "Google开源能自我改进的智能体框架「Harness²」",
      "normalized_summary": "Harness² 在固定模型权重的条件下递归优化提示词、工具、记忆、技能及编排，包含当前任务优化和跨任务经验积累两个层次。",
      "availability": "GitHub 代码、安装说明、本地演示及基准运行流程已公开。",
      "code_license": "Apache-2.0",
      "weights_status": "not_applicable",
      "verification_status": "verified",
      "caveats": [
        "是智能体运行框架，不是新基础模型或训练权重发布。",
        "官方明确它不是 Google 正式支持的产品；第三方组件和数据沿用原许可。",
        "README 报告的提升限于所测模型、执行框架及基准，不能直接改写成全面最强。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/google-research/harness2",
          "label": "Google Research Harness² 官方仓库"
        }
      ],
      "source_timestamp_seconds": null,
      "verified_on": "2026-10-26",
      "classification": {
        "section": "开发工具与基础设施",
        "subtype": "智能体框架",
        "use_cases": [
          "智能体开发",
          "自动优化"
        ],
        "technical_tags": [
          "固定模型权重",
          "递归优化"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 6,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://github.com/google-research/harness2"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-knowledge-work-plugins",
      "entity_name": "Knowledge Work Plugins",
      "entity_type": "skill",
      "organization": "Anthropic",
      "original_claim": "Anthropic开源11个岗位技能「knowledge-work-plugins」",
      "normalized_summary": "Anthropic 的知识工作插件集合，将技能、连接器、命令和子智能体组合为岗位工作流，主要面向 Claude Cowork，也兼容 Claude Code。",
      "availability": "公开 GitHub 仓库；可浏览、安装及定制插件。",
      "code_license": "Apache-2.0",
      "weights_status": "not_applicable",
      "verification_status": "partially_verified",
      "caveats": [
        "对象是插件/技能集合，不是新模型。",
        "仓库开源不表示 Claude 服务或所连接的第三方服务免费。",
        "此处验证当前仓库状态，尚未单独确定作者所指的具体本周更新或新增插件清单。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/anthropics/knowledge-work-plugins",
          "label": "Anthropic Knowledge Work Plugins 官方仓库"
        }
      ],
      "source_timestamp_seconds": null,
      "verified_on": "2026-10-26",
      "classification": {
        "section": "Skills与插件",
        "subtype": "岗位插件与技能集合",
        "use_cases": [
          "办公自动化",
          "知识工作"
        ],
        "technical_tags": [
          "连接器",
          "技能与命令",
          "子智能体"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 7,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://github.com/anthropics/knowledge-work-plugins"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-cinetic",
      "entity_name": "Cinetic",
      "entity_type": "skill",
      "organization": "Leonxlnx",
      "original_claim": "工程师开源AI做视频技能「Cinetic」",
      "normalized_summary": "Cinetic 是 MIT 许可的 AI 视频制作技能，使用 Remotion、HyperFrames 等工具组织视频制作流程。",
      "availability": "GitHub 代码与 Skill 可获取。",
      "code_license": "MIT",
      "weights_status": "not_applicable",
      "verification_status": "verified",
      "caveats": [
        "属于 Skill 和视频制作工作流，不是视频生成基础模型。",
        "其调用的工具、服务和模型可能有各自的使用条件。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/Leonxlnx/cinetic",
          "label": "Cinetic 官方 GitHub 仓库与 README"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "Skills与插件",
        "subtype": "视频制作Skill",
        "use_cases": [
          "视频制作"
        ],
        "technical_tags": [
          "程序化视频"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 8,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://github.com/Leonxlnx/cinetic"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-tv-vibehack",
      "entity_name": "tv-vibehack / Clean Your TV",
      "entity_type": "application",
      "organization": "Gathin23",
      "original_claim": "工程师开源电视清理技能「tv-vibehack」",
      "normalized_summary": "Clean Your TV 提供提示词、脚本和启动器，让编程助手通过 Wi-Fi/ADB 清理 Android 或 Google TV 的预装干扰并更换桌面；README 确认旧名为 tv-vibehack。",
      "availability": "MIT 代码公开，可按项目文档自行使用；无需新模型权重。",
      "code_license": "MIT",
      "weights_status": "not_applicable",
      "verification_status": "verified",
      "caveats": [
        "README 说明仓库在 2026 年 10 月 19 日前使用 tv-vibehack 名称；两个名称应聚合为同一实体。",
        "是电视工具与 AI 编程助手工作流，不是电视专用 AI 基础模型。",
        "平台功能有差异，不能概括为所有电视都支持相同改造。字体采用独立 OFL 许可。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/Gathin23/cleanyourtv",
          "label": "Clean Your TV 官方仓库（README 记录旧名）"
        },
        {
          "kind": "license",
          "url": "https://github.com/Gathin23/cleanyourtv/blob/main/LICENSE",
          "label": "Clean Your TV MIT 许可证"
        }
      ],
      "source_timestamp_seconds": null,
      "verified_on": "2026-10-26",
      "classification": {
        "section": "应用与智能体",
        "subtype": "电视工具",
        "use_cases": [
          "电视清理",
          "设备管理"
        ],
        "technical_tags": [
          "ADB",
          "AI编程工作流"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 9,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://github.com/Gathin23/cleanyourtv"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-gpt-image-3",
      "entity_name": "GPT Image 3",
      "entity_type": "model",
      "organization": "OpenAI",
      "original_claim": "OpenAI 内测「GPT Image 3」",
      "normalized_summary": "作者引用 TestingCatalog 对 Aurora 测试迹象的报道，推测其可能为 GPT Image 3；报道明确这仍是猜测，目前未找到对应的 OpenAI 官方确认。",
      "availability": "未核实；不能据此认定已发布、可申请测试或 API 可用。",
      "code_license": "未核实",
      "weights_status": "unverified",
      "verification_status": "unverified",
      "caveats": [
        "保留为原视频报道的待核实条目，不能写成官方已发布新闻。",
        "暂无可支持该具体名称与内测状态的 OpenAI 官方来源。"
      ],
      "sources": [
        {
          "kind": "third_party_report",
          "url": "https://www.testingcatalog.com/openai-possibly-testing-gpt-image-3/",
          "label": "TestingCatalog：Aurora 可能为 GPT Image 3（第三方推测，非官方确认）"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "图像模型",
        "use_cases": [
          "图像生成"
        ],
        "technical_tags": [],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-26",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 10,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://www.testingcatalog.com/openai-possibly-testing-gpt-image-3/"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-ideogram-vector-1",
      "entity_name": "Ideogram Vector 1.0",
      "entity_type": "model",
      "organization": "Ideogram",
      "original_claim": "Ideogram推出矢量图模型「Vector 1.0」",
      "normalized_summary": "Ideogram 提供矢量图生成模型和生成 SVG 的 API，API 模型标识为 ideogram-vector-1。",
      "availability": "商业网页与 API 可用。",
      "code_license": "未见公开代码许可证",
      "weights_status": "not_verified_public",
      "verification_status": "verified",
      "caveats": [
        "未核实模型权重开源；可通过网页或 API 使用不等于可本地部署。",
        "展示名称和 API 模型标识分别保留，避免按名称猜测接口。"
      ],
      "sources": [
        {
          "kind": "official_product",
          "url": "https://ideogram.ai/models/vector/",
          "label": "Ideogram Vector 官方模型页"
        },
        {
          "kind": "official_docs",
          "url": "https://developer.ideogram.ai/api-reference/vectors/generate-svg",
          "label": "Ideogram 生成 SVG API 文档"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "矢量图模型",
        "use_cases": [
          "视觉设计",
          "矢量图生成"
        ],
        "technical_tags": [],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 11,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://ideogram.ai/models/vector/"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-fibo-2",
      "entity_name": "FIBO 2",
      "entity_type": "model",
      "organization": "Bria",
      "original_claim": "Bria开源最强图像编辑模型「FIBO 2」",
      "normalized_summary": "Bria 提供 Fibo-2.0-dev 与 Fibo-2.0-edit-turbo 模型权重；相关模型卡标明非商业用途限制。",
      "availability": "Hugging Face 模型权重可获取，使用须遵守相应模型条款。",
      "code_license": "代码许可证未单独核实",
      "weights_status": "available_noncommercial",
      "verification_status": "partially_verified",
      "caveats": [
        "权重可下载不等于采用不限制商业用途的开源许可证。",
        "“最强”未独立验证。",
        "Fibo-2.0-dev 与 Fibo-2.0-edit-turbo 是不同变体，应保留各自模型卡与条款。"
      ],
      "sources": [
        {
          "kind": "model_weights",
          "url": "https://huggingface.co/briaai/Fibo-2.0-dev",
          "label": "Bria Fibo-2.0-dev 官方模型卡"
        },
        {
          "kind": "model_weights",
          "url": "https://huggingface.co/briaai/Fibo-2.0-edit-turbo",
          "label": "Bria Fibo-2.0-edit-turbo 官方模型卡"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "图像生成与编辑模型",
        "use_cases": [
          "视觉设计",
          "图像生成",
          "图像编辑"
        ],
        "technical_tags": [],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 12,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://huggingface.co/briaai/Fibo-2.0-dev"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      },
      "weights_license": "非商业使用许可；详见官方模型卡条款"
    },
    {
      "id": "2026-10-25-wevisone-vl",
      "entity_name": "WeVisOne-VL",
      "entity_type": "model",
      "organization": "Tencent WeChat Vision（腾讯微信视觉团队）",
      "original_claim": "腾讯开源视觉模型「WeVisOne-VL」",
      "normalized_summary": "WeVisOne-VL 统一目标检测、定位、计数、OCR、分割和 alpha 抠图。官方已公开 2B/4B 权重、推理包及评测流程，Hugging Face 模型卡标注 Apache-2.0。",
      "availability": "GitHub 代码及 2B/4B 模型权重公开；提供在线演示和本地推理示例。",
      "code_license": "Apache-2.0（腾讯自有代码；第三方组件另行遵循原许可）",
      "weights_status": "available",
      "verification_status": "verified",
      "caveats": [
        "官方模型卡当前定位单轮图像感知；不应扩展为视频理解模型。"
      ],
      "sources": [
        {
          "kind": "code_repository",
          "url": "https://github.com/Tencent/WeVisOne-VL",
          "label": "腾讯 WeVisOne-VL 官方仓库"
        },
        {
          "kind": "model_weights",
          "url": "https://huggingface.co/tencent/WeVisOne-VL-2B",
          "label": "腾讯 WeVisOne-VL-2B 官方模型卡与权重"
        },
        {
          "kind": "model_weights",
          "url": "https://huggingface.co/tencent/WeVisOne-VL-4B",
          "label": "腾讯 WeVisOne-VL-4B 官方模型卡与权重"
        },
        {
          "kind": "license",
          "url": "https://github.com/Tencent/WeVisOne-VL/blob/main/LICENSE",
          "label": "腾讯 WeVisOne-VL 代码许可证"
        }
      ],
      "source_timestamp_seconds": null,
      "verified_on": "2026-10-26",
      "classification": {
        "section": "模型",
        "subtype": "视觉语言模型",
        "use_cases": [
          "图像理解",
          "目标检测",
          "OCR",
          "分割与抠图"
        ],
        "technical_tags": [
          "视觉语言建模"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "weights_license": "Apache-2.0（官方 2B/4B 模型卡）",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 13,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://github.com/Tencent/WeVisOne-VL"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-hy-nomas",
      "entity_name": "Hy-Nomas",
      "entity_type": "model",
      "organization": "Tencent Hunyuan（腾讯混元）",
      "original_claim": "腾讯开源世界模型「Hy-Nomas」",
      "normalized_summary": "腾讯混元公开 Hy-Nomas 交互式视频世界生成模型、训练与推理代码及模型权重，支持多轮自由文本指令和相机轨迹控制。",
      "availability": "训练、推理、交互演示和数据标注代码已公开；Hugging Face 权重可下载，并提供在线交互演示。",
      "code_license": "Apache-2.0；第三方组件保留其原许可证。",
      "weights_status": "released",
      "weights_license": "Apache-2.0（腾讯公开的本项目代码、参数和权重；第三方组件各自许可）",
      "verification_status": "verified",
      "caveats": [
        "官方技术报告当前标注 Coming Soon。",
        "官方提供单 RTX 4090 低内存配置，但依赖 INT8、CPU offload 和滑动窗口，所需系统内存及峰值显存受配置影响。",
        "未独立验证生成质量、速度或“最强”表述。"
      ],
      "sources": [
        {
          "kind": "official_repository",
          "url": "https://github.com/Tencent-Hunyuan/Hy-Nomas",
          "label": "Hy-Nomas 官方仓库"
        },
        {
          "kind": "official_weights",
          "url": "https://huggingface.co/tencent/Hy-Nomas",
          "label": "腾讯官方模型权重"
        },
        {
          "kind": "official_license",
          "url": "https://github.com/Tencent-Hunyuan/Hy-Nomas/blob/main/LICENSE",
          "label": "Apache-2.0 及第三方许可范围"
        },
        {
          "kind": "official_demo",
          "url": "https://hy-nomas.hy.tencent.com/demo",
          "label": "官方交互演示"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "世界模型",
        "use_cases": [
          "交互世界生成",
          "视频生成",
          "相机控制"
        ],
        "technical_tags": [
          "自回归分段生成",
          "扩散",
          "蒸馏",
          "LoRA"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-26",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 14,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://github.com/Tencent-Hunyuan/Hy-Nomas"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-hi3d-v1-0",
      "entity_name": "Hi3D v1.0",
      "entity_type": "model",
      "organization": "Hi3D",
      "original_claim": "研究员发布最强开源3D生成模型「Hi3D 1.0」",
      "normalized_summary": "Hi3D 发布基于 Sparc3D 的三维几何细化模型，以同一物体的参考图和粗网格为输入，逐级输出高分辨率几何网格；已公开推理代码和模型权重。",
      "availability": "推理代码、模型权重与技术报告已公开；README 记录发布日为 2026-10-23。训练代码和论文评测框架未包含。",
      "code_license": "Hi3D Open License Agreement v1.0；原始及第三方部分继续适用 Apache-2.0/MIT 等原条款。",
      "weights_status": "released",
      "weights_license": "Hi3D Open License Agreement v1.0（自定义、附条件商用）",
      "verification_status": "partially_verified",
      "caveats": [
        "该项目主要是第二阶段几何细化，并非仅凭一句文字即可完成所有 3D 工作流；只生成几何，不生成纹理、材质或顶点色。",
        "自定义许可允许附条件商用；商业集成要求品牌展示，超过规定用户量或营收门槛需申请另行书面许可，不能标为无条件 Apache/MIT 开源。",
        "README 表示 1536³ 路径仅在 96GB H20 上验证，不能承诺普通消费级显卡同等运行。",
        "1536³ 表示稀疏提取网格分辨率，不是固定面数；本次未复现性能排名。"
      ],
      "sources": [
        {
          "kind": "official_repository",
          "url": "https://github.com/hi3d-official/Hi3Dv1.0",
          "label": "Hi3D v1.0 官方推理仓库"
        },
        {
          "kind": "official_weights",
          "url": "https://huggingface.co/hi3d-official/Hi3Dv1.0",
          "label": "Hi3D 官方权重"
        },
        {
          "kind": "official_license",
          "url": "https://github.com/hi3d-official/Hi3Dv1.0/blob/main/LICENSE",
          "label": "Hi3D Open License v1.0"
        },
        {
          "kind": "official_report",
          "url": "https://github.com/hi3d-official/Hi3Dv1.0/blob/main/docs/Hi3D_v1.0_Technical_Report.pdf",
          "label": "官方技术报告（README 所链接，未审读全文）"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "3D生成与重建模型",
        "use_cases": [
          "三维几何细化",
          "图像条件建模"
        ],
        "technical_tags": [
          "Sparc3D",
          "稀疏表示",
          "分级细化"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-26",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 15,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://github.com/hi3d-official/Hi3Dv1.0"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-sky-001",
      "entity_name": "SKY-001",
      "entity_type": "model",
      "organization": "Skyfall",
      "original_claim": "研究员开源工程世界模型「SKY-001」",
      "normalized_summary": "Skyfall 展示面向工程、CAD 和 BIM 的 SKY-001 世界模型，并提供候补名单；本次未找到官方代码或权重公开发布。",
      "availability": "官方展示与候补名单；公开下载和普遍访问状态未核实。",
      "code_license": "未见公开代码许可证",
      "weights_status": "not_verified_public",
      "verification_status": "partially_verified",
      "caveats": [
        "项目存在及定位有官方页面支持，但原视频的“开源”声明未获已找到的一手来源支持。",
        "未找到公开发布证据不等于证明项目永久不开放，状态应随新来源更新。"
      ],
      "sources": [
        {
          "kind": "official_product",
          "url": "https://skyfall.ai/sky-001",
          "label": "Skyfall SKY-001 官方页面"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "工程世界模型",
        "use_cases": [
          "工程设计"
        ],
        "technical_tags": [
          "世界模型"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 16,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://skyfall.ai/sky-001"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-fasth3-omni",
      "entity_name": "FastH3 Omni",
      "entity_type": "model",
      "organization": "FastVideo / Hao AI Lab 与 Nuva Lab",
      "original_claim": "研究员开源极速视频模型「FastH3 Omni」",
      "normalized_summary": "FastH3 Omni 发布用于音画同步生成的模型权重，可结合文本与图像、视频、音频参考输入，通过八次 Transformer 评估生成带声音的视频，并提供不同精度和运行时版本。",
      "availability": "官方集合包含 BF16、FP8、NVFP4 QAD、ComfyUI 及 MLX 等版本；BF16 权重公开可下载，运行依赖对应推理框架及 MiniMax-H3 共享组件。",
      "code_license": "FastVideo 运行框架为 Apache-2.0；不能将框架许可证套用于模型权重。",
      "weights_status": "released",
      "weights_license": "MiniMax H3 Community License Agreement（自定义，包含地域及商业使用条款）",
      "verification_status": "partially_verified",
      "caveats": [
        "模型权重许可有地域限制及商业条件，不属于无条件宽松开源。",
        "不同 BF16、FP8、NVFP4、MLX 版本的硬件要求和结果不同，不能以一个版本的速度/显存概括整个系列。",
        "BF16 模型卡说明参考条件输入至少需要一张图像或一段视频；可用请求长度和尺寸依运行时及内存而定。",
        "本次核验未复现模型质量、推理速度及排名。"
      ],
      "sources": [
        {
          "kind": "official_collection",
          "url": "https://huggingface.co/collections/FastVideo/fasth3-omni",
          "label": "FastH3 Omni 官方版本集合"
        },
        {
          "kind": "official_weights",
          "url": "https://huggingface.co/FastVideo/FastVideo-FastH3-Omni-8-Step-V1",
          "label": "BF16 发布权重及模型卡"
        },
        {
          "kind": "official_repository",
          "url": "https://github.com/hao-ai-lab/FastVideo",
          "label": "FastVideo 推理与训练框架"
        },
        {
          "kind": "official_license",
          "url": "https://huggingface.co/MiniMaxAI/MiniMax-H3/blob/main/LICENSE",
          "label": "模型权重适用的 MiniMax H3 社区许可"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "视频生成模型",
        "use_cases": [
          "音画同步生成",
          "参考视频生成"
        ],
        "technical_tags": [
          "多模态参考",
          "八步推理",
          "量化",
          "蒸馏"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-26",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 17,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://huggingface.co/collections/FastVideo/fasth3-omni"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-underdog-bark-3-0",
      "entity_name": "Underdog Bark 3.0",
      "entity_type": "model",
      "organization": "Conway Research",
      "original_claim": "研究员开源极速语音识别模型「Underdog Bark 3.0」",
      "normalized_summary": "Conway Research 公开 Underdog Bark 3.0 英语语音识别模型，以约 163MB 压缩文件分发 0.6B 参数模型，支持设备端转写，并提供 PyTorch、MLX 等运行路径。",
      "availability": "模型权重与加载/转写脚本在 Hugging Face 公开；支持本地推理，具体平台能力依所选运行时。",
      "code_license": "加载脚本已公开；未单独核实脚本许可。",
      "weights_status": "released",
      "weights_license": "CC-BY-4.0",
      "verification_status": "verified",
      "caveats": [
        "这是语音转文字 ASR 模型，只支持英语；不能误分为文本转语音或声音生成模型。",
        "约 163MB 是压缩权重下载大小，不等于运行 RAM/VRAM；PyTorch 路径会解包至 FP32。",
        "模型卡中的 WER 与领先性是作者基于指定七个英语测试集的报告，Bark 各行当时尚未收录至该排行榜；本次未独立复现。",
        "长音频会提高内存需求，模型卡建议小内存设备分段处理。"
      ],
      "sources": [
        {
          "kind": "official_weights",
          "url": "https://huggingface.co/ConwayResearch/Underdog-Bark-3.0",
          "label": "Underdog Bark 3.0 模型卡与权重"
        },
        {
          "kind": "official_attribution",
          "url": "https://huggingface.co/ConwayResearch/Underdog-Bark-3.0/blob/main/NOTICE",
          "label": "模型来源、变更与 CC-BY-4.0 署名说明"
        },
        {
          "kind": "official_files",
          "url": "https://huggingface.co/ConwayResearch/Underdog-Bark-3.0/tree/main",
          "label": "公开权重与推理脚本文件列表"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "语音识别模型",
        "use_cases": [
          "语音转写",
          "设备端语音识别"
        ],
        "technical_tags": [
          "ASR",
          "英语",
          "低比特压缩",
          "MLX"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-26",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 18,
        "listed_in_description": false,
        "author_cited_urls": [
          "https://huggingface.co/ConwayResearch/Underdog-Bark-3.0"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    },
    {
      "id": "2026-10-25-dessa",
      "entity_name": "Dessa",
      "entity_type": "model",
      "organization": "Block",
      "original_claim": "Block发布最强语音对话模型「Dessa」",
      "normalized_summary": "Block 展示全双工语音到语音模型 Dessa，并面向少数 AI 安全研究者提供早期访问。",
      "availability": "有限早期访问；未见公开 API、代码或模型权重。",
      "code_license": "未见公开代码许可证",
      "weights_status": "not_verified_public",
      "verification_status": "partially_verified",
      "caveats": [
        "不能将面向少数研究者的早期访问标记为公众全面可用。",
        "“最强”未独立验证，需关联具体基准和测试条件。"
      ],
      "sources": [
        {
          "kind": "official_product",
          "url": "https://block.xyz/dessa",
          "label": "Block Dessa 官方页面"
        }
      ],
      "source_timestamp_seconds": null,
      "classification": {
        "section": "模型",
        "subtype": "语音对话模型",
        "use_cases": [
          "语音交互"
        ],
        "technical_tags": [
          "全双工语音"
        ],
        "basis": "editorial_classification_v2",
        "note": "按主要交付物分类；用途与技术特征作为独立标签。"
      },
      "verified_on": "2026-10-25",
      "provenance": {
        "source_kind": "author_summary_image",
        "summary_image_order": 19,
        "listed_in_description": true,
        "author_cited_urls": [
          "https://block.xyz/dessa"
        ],
        "comment_id": "321871171184",
        "transcription_status": "visually_reviewed",
        "reviewer_type": "ai_assistant"
      }
    }
  ],
  "taxonomy": {
    "version": 2,
    "sections": [
      "模型",
      "应用与智能体",
      "开发工具与基础设施",
      "Skills与插件",
      "机器人与硬件",
      "研究成果",
      "产业与治理"
    ],
    "primary_grouping": "classification.section",
    "object_form": "entity_type",
    "secondary_facets": [
      "classification.use_cases",
      "classification.technical_tags",
      "verification_status",
      "availability",
      "code_license",
      "weights_status"
    ],
    "classification_note": "产品与项目按主要交付形态归入稳定栏目；用途与技术机制各自独立。研究成果及产业与治理承接非产品新闻。主题聚合允许一条记录进入多个组。",
    "entity_resolution_note": "按机构、项目标识、版本及官方来源消歧；不同机构的同名Duet不可自动合并。"
  },
  "verification_note": "核验状态针对各条项目说法；来源完整性单独记录。各条 verified_on 记录实际核验日期；图文对齐不等于事实核实。"
}