免费 / 开源在本地或云端运行和构建开源 AI 模型
Label Studio: 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。 Label Studio 记录了 137,199 月访问量,月度环比增长为 -16.1%,定价为定价请咨询,免费。Scale 记录了 616,915 月访问量,增长率为 +12.5%,定价为定价请咨询。

Label Studio is an open-source data labeling and AI evaluation platform from HumanSignal. It handles images, video, audio, text, documents, time series and agent traces in one flexible workspace, and connects to your ML pipeline through an API, Python SDK and webhooks.
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.
| 维度 / 指标 | ![]() | |
|---|---|---|
| 官方域名 | labelstud.io | scale.com |
| 定价模式 | 定价请咨询,免费 | 定价请咨询 |
| 月访问量 | 13.72万 (137,199) | 61.69万 (616,915) |
| 月度环比流量变化 | -2.63万 (-16.1%) | +6.87万 (+12.5%) |
| 主要市场与份额 | 🇺🇸 美国 (23.9%) | 🇺🇸 美国 (44.2%) |
| 直接访问 / 月 | 4.71万 | 19.14万 |
| 用户评分 | 4.7 | 4.7 |
| 支持的平台 | 网站 | 网站 |

Label Studio is an open-source data labeling and AI evaluation platform from HumanSignal. It handles images, video, audio, text, documents, time series and agent traces in one flexible workspace, and connects to your ML pipeline through an API, Python SDK and webhooks.
Programmable interfaces and custom templates let one workspace handle images, video, audio, text, PDFs, time series and multi-modal tasks.
Build custom benchmarks and rubrics, run side-by-side model comparisons, and grade generated answers against retrieved sources for RAG evaluation.
Collect human preferences, corrections and rankings to feed reinforcement learning from human feedback and fine-tuning workflows.
Connect observability tools, storage and any model to power AI-assisted pre-labeling, benchmarking and continuous evaluation.
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.
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。

专项更强软件与真人专家协同运作的企业级 AI 基础设施

免费 / 开源Open WebUI is an open-source, self-hosted AI interface that lets individuals and organizations run any model — local or cloud — inside a workspace they fully control. It ships as a one-command install, supports Ollama, OpenAI-compatible and Anthropic endpoints, and extends through Python tools, functions and pipelines.
免费 / 开源Open WebUI is an open-source, self-hosted AI interface that lets individuals and organizations run any model — local or cloud — inside a workspace they fully control. It ships as a one-command install, supports Ollama, OpenAI-compatible and Anthropic endpoints, and extends through Python tools, functions and pipelines.
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.
专项更强构建、模拟、评估并监控可自我改进的 AI 智能体