JevRouter实现多模型协同编程
JevRouter自动匹配最优模型，用99%的Opus 5.5和GPT-6 Astra性能实现40%成本节省。
JevRouter让多个AI模型在同一Codex会话中协同工作。Opus 5.
5负责规划，GPT-6 Astra构建后端，Kimi K3开发前端，DeepSeek处理测试，GLM 5.3 Flash编写文档。
这种协作方式使构建成本降低40%，速度提升15%。
This is what the future of coding looks like. Multiple AI models working in the same Codex session, with Jev routing them to tackle different parts of the task. Here, I had it build a full-stack demo app: > Opus 5.5 planned it. > GPT-6 Astra built the backend. > Kimi K3 built the frontend. > DeepSeek handled testing. > GLM 5.3 Flash wrote the docs. Jev handles the switching. I never touched the model picker. 40% cheaper, 15% faster for the same build.
This report is categorized under AITOP's "Products" desk. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include JevRouter, Opus 5.5, GPT-6 Astra, coding assistants.
Source attribution: curated from elvis (@omarsar0). Cross-source corroboration: 11 independent sources have covered this development (including kimmonismus, Garry Tan, 歸藏(guizang.ai)), confirming industry-wide signal strength.
