Cloudflare open-sources Clef decision models for AI agents
Cloudflare released Clef, a family of open-weight models that pick among predefined options instead of generating text, in 27B-parameter and 9B-parameter (Clef-Flash) versions, InfoQ reports. The 27B multimodal model takes a state plus a schema of typed questions, handles text, JSON, images or video, and returns probabilities for all options in a single forward pass, while Clef-Flash targets latency-sensitive decisions; Cloudflare's own benchmark puts Clef-Flash at 38.8 ms median latency versus 209.3 ms for the 27B model. Weights are downloadable on Hugging Face and the models are served through Workers AI, alongside a fine-tuning service staffed initially by Cloudflare engineers, and the API is compatible with Typesafe AI's Jev System One, though Hacker News and Reddit commenters questioned public benchmarks and whether the models know when to abstain.
Cloudflare says hosting Clef on its edge GPUs yields lower network latency, allowing the models to sit in an agent's core decision path alongside an LLM on Workers AI.
在近期的“生日周”活动中，Cloudflare 发布了 Clef"，这是一组开源权重 AI 模型，用于在预设选项之间做出选择，而不是生成文本。Cloudflare 发布了 90 亿参数和 270 亿参数版本的模型，以及一个将它们适配到特定决策任务的平台。
Clef 是一款 270 亿参数的多模态模型，它接收状态和带类型问题的 Schema 作为输入，并输出决策结果。它可以处理文本、JSON、图像或视频，只需一次前向推理就能返回针对每个问题的所有可选项对应的概率，无需生成自由文本或解析输出。
#Cloudflare#Clef#Clef-Flash#Workers AI#Hugging Face#Typesafe AI#Jev System One