Hermes Agent runs Agents-A1 offline
AICodeKing released a video demonstrating how to combine Shanghai AI Lab's latest 35B Mixture-of-Experts (MoE) agentic model, Agents-A1, with Nous Research's persistent, self-improving Hermes Agent framework. Running these models locally—paired with editors like Zed—allows developers to set up a fully local coding assistant that supports robust, offline tool calling, persistent multi-session memory, and autonomous skill acquisition without relying on cloud-based frontier APIs.
Local developer workflows are transitioning from simple chat completions to fully agentic, self-optimizing environments that match closed-source model performance. By focusing on scaling the knowledge-action horizon rather than parameter count, models like Agents-A1 deliver trillion-parameter-level agentic capabilities on consumer hardware. When paired with persistent frameworks like Hermes Agent and high-performance local editors like Zed, this setup eliminates API costs, ensures source code privacy, and represents a viable, zero-latency, local-first alternative to commercial tools like GitHub Copilot.
DISCOVERED
2h ago
2026-07-04
PUBLISHED
2h ago
2026-07-04
RELEVANCE
AUTHOR
aicodeking