Nous Research introduces Hermes, an open-source autonomous agent that learns and improves with each task it performs. Since its release, Hermes has garnered over 5K GitHub stars and sparked debates within the AI community about whether it outperforms OpenClaw.
Hermes is built on Nous’ Hermes-3 model family, which uses Llama 3.1 and their Atropos RL stack. It features 47 built-in tools, a persistent memory system, MCP server integration, voice mode support, and a skills system for creating, updating, and deleting procedures autonomously.
As users interact with Hermes, the agent saves non-trivial workflows as reusable skill documents, enhancing its capabilities over time. Its latest release includes background task notifications, freeMiMo v2 Pro on Nous Portal, and live model switching across platforms, supporting models like Claude, ChatGPT, Qwen, and local open-source options.
While OpenClaw focuses on ecosystem integration with tools like Cursor and Claude Code IDEs, Hermes prioritizes self-improvement. It boasts a lightweight architecture resulting in lower latency and faster response times compared to OpenClaw’s occasionally sluggish performance.
Hermes supports the Agent Communication Protocol (ACP) for interaction with other agents but does not focus on orchestration. Users can run both agents simultaneously, utilizing OpenClaw for orchestration and Hermes for execution.
OpenClaw has invested in subagent architecture, whereas Hermes excels as a standalone executor. Its ability to create and modify its own skills means users are shielded from potentially unsafe third-party skills.
Both agents support multiple messaging platforms, but Hermes offers more flexible deployment options, running on devices ranging from Raspberry Pi to cloud clusters. Both are open-source and free, with costs limited to API calls or electricity for local models.
OpenClaw’s extensive documentation reflects its larger community and development history, while Hermes’ documentation is engineer-focused. OpenClaw has seen widespread adoption by companies like Xiaomi and Nvidia, whereas Hermes appeals more to technical enthusiasts.
Deployment choices are crucial as both agents can access significant system resources. Hermes runs with the privileges of its launch account and advises against running the gateway as root. OpenClaw’s sandbox model is still being refined for security.
Installing Hermes is straightforward: a single terminal command sets up everything needed, avoiding common setup issues. Users can configure their agent quickly, select AI models via Nous Portal or OpenRouter, and run entirely on open models like Qwen or DeepSeek.
To connect Hermes to Telegram, create a bot using @BotFather, obtain the token, and integrate it with Hermes’ gateway for seamless communication across platforms. This setup allows users to interact with Hermes from anywhere, leveraging features like voice memo support and group chat capabilities.