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一位开发者公开了他的个人 AI 工作流网页，详细讲解如何用 Markdown 约定、UserPromptSubmit 钩子和外包脚本在 Claude、Codex、Kimi、Grok、Gemini 等多模型间做任务派单、成本分层与自动验收，形成一套被称为 harness 的第四代实践体系。
SupraLabs releases Supra-Router-51M, a tiny 51M parameter model for routing prompts to appropriate larger or smaller models, enabling low-latency orchestration. A companion dataset is also released.
SupraLabs releases Supra-Router-51M, a 51.7M parameter micro-LLM for multi-task infrastructure routing, designed to decide whether to process prompts locally on edge or send them to cloud-hosted models. Fine-tuned on a small dataset, it uses multi-task sequence generation for robust routing.
The article explores the challenge of per-prompt model routing in AI agents, questioning whether anyone has effectively solved it. It points out that current practices rely on gut feeling, flat-rate plans reduce pressure to optimize, and a triage layer may introduce its own costs.
Factory Router automatically selects the best AI model for each task, claiming to cut costs by 25% while maintaining frontier performance, a promising tool for large enterprises.