免费 / 开源在本地或云端运行和构建开源 AI 模型
Scale 记录了 616,915 月访问量,月度环比增长为 +12.5%,定价为定价请咨询。Vana 记录了 5,701 月访问量,增长率为 -45.5%,定价为免费。
Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.
Scale is an enterprise AI company that supplies the data, evaluation and deployment layers behind production AI. Its Data Engine sources and labels training data for frontier models, its evaluation work benchmarks model capability, and its platform teams help enterprises and governments move AI systems from pilot into real operations.
Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.

让用户拥有并授权 AI 所用数据的开放数据基础设施
用户通过开源连接器从已在使用的服务中收集数据,数据始终保存在自己的设备或自己控制的加密存储中。
本地运行的访问引擎对数据加密,仅在存在有效链上许可时释放数据,每次读取都会写入可审查的访问日志。
安装 @opendatalabs/vana-sdk 即可请求用户批准的数据、从个人服务器读取,并从应用托管余额结算协议费用。
群体可汇集数据用于隐私保护的计算任务,让 AI 使用贡献数据而不暴露原始记录。
免费 / 开源在本地或云端运行和构建开源 AI 模型
免费 / 开源ModelScope (魔搭社区) is an open-source AI community and model service platform that hosts thousands of pretrained models, datasets, and ready-to-run demos, backed by Alibaba Cloud infrastructure.
免费 / 开源ModelScope (魔搭社区) is an open-source AI community and model service platform that hosts thousands of pretrained models, datasets, and ready-to-run demos, backed by Alibaba Cloud infrastructure.
专项更强简化计算机视觉数据集标注与模型训练,但不太适合通用的 LLM 文本任务。
专注于企业级数据标注和训练数据整理,类似于 Scale 的核心标注业务。
提供企业级多模态标注和数据管理工具,但对托管式标注人力的强调较少。

专项更强在互联环境中跟踪、评估并交付 AI 模型与智能体。

专项更强Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.
专项更强Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation.

免费 / 开源提供灵活的开源替代方案,适用于自定义数据标注和人机回环(Human-in-the-loop)标注管道。