A new open-source AI agent called Hermes Agent is bringing self-improving artificial intelligence to Raspberry Pi computers, letting users run a learning AI assistant locally without relying on cloud services. Built by Nous Research, the same team behind high-quality fine-tuned language models, Hermes Agent stands apart from simple chatbots because it automatically learns from conversations, creates new skills on its own, and maintains long-term memory that persists across sessions.

Unlike basic AI tools that simply respond to commands, Hermes Agent functions as a true agentic AI, meaning it can plan multi-step tasks, execute shell commands on your Raspberry Pi, call APIs, and return structured responses all from a single message sent through Telegram, Discord, or WhatsApp. For the underlying language model, users can either run Ollama locally for complete privacy or connect to cloud providers like OpenRouter, Anthropic, or OpenAI if they prefer.

What Hardware Do You Need to Run Hermes Agent Locally?

The beauty of Hermes Agent is that it works across different Raspberry Pi models, though the experience varies based on your hardware. For the smoothest operation with local models, Nous Research recommends specific configurations:

• Optimal Setup: Raspberry Pi 5 with 8 GB of RAM, which provides enough memory to run Ollama's 3B parameter models alongside the agent's learning loop without slowdowns
• Budget Alternative: Raspberry Pi 4 with 4 GB of RAM, which works well if you use cloud-based language models or stick to very small 1B models through Ollama
• Storage Solution: NVMe SSD with PCIe HAT instead of a microSD card, since model files take 1 to 4 GB and the agent's long-term memory grows quickly over time
• Cooling: Official Active Cooler for Pi 5, because running both Hermes Agent and Ollama keeps all four processor cores busy continuously

The software requirements are straightforward: Raspberry Pi OS in 64-bit format, curl, Python 3.11, and an active internet connection for initial setup. A Telegram or Discord account is optional but highly recommended for controlling your AI assistant remotely.

How to Install and Configure Hermes Agent on Your Raspberry Pi

The installation process is remarkably simple, requiring just a single command with no administrator privileges needed. The setup script automatically handles Python package management, downloads the necessary code, and configures everything:

• Installation Command: Run a single curl command that installs uv (a Python package manager), Python 3.11, clones the Hermes Agent repository, and sets up all dependencies automatically
• Memory Optimization: For Raspberry Pi 4 users with 4 GB of RAM, switch the memory storage from ChromaDB to SQLite immediately after installation to save 200 to 300 MB of RAM and prevent out-of-memory errors
• Model Selection: Use the interactive setup wizard to choose between local Ollama models or cloud providers, with the ability to switch providers and models at any time
• Recommended Local Models: llama3.2:1b for simple commands at over 30 tokens per second, llama3.2:3b for the best balance on Pi 5 at 8 to 12 tokens per second, or mistral:7b for highest quality if you have 8 GB RAM available
• Messenger Integration: Connect Telegram, Discord, or WhatsApp so you can control your Pi from anywhere without needing a VPN or open ports
• Automatic Restart: Create a systemd service file to ensure Hermes Agent restarts automatically after your Raspberry Pi reboots

How Does Hermes Agent Learn and Improve Over Time?

What makes Hermes Agent fundamentally different from other local AI tools is its built-in learning mechanism. Every conversation the agent has gets saved to long-term memory, and the agent automatically creates new skills from each interaction, refining them as needed. When you start a new session, Hermes remembers the context from previous conversations, allowing it to build on past knowledge and improve its responses over time.

The agent comes with over 70 built-in skills for common tasks, but it can teach itself new ones based on how you interact with it. This self-improving capability is what separates Hermes Agent from simpler alternatives like OpenClaw, which is lighter weight but lacks cross-session memory and learning features.

Local AI Versus Cloud: Which Approach Makes Sense?

Hermes Agent gives users a genuine choice between privacy and convenience. Running Ollama locally on your Raspberry Pi means your conversations, commands, and the agent's learned skills never leave your home network, providing complete data privacy. However, this requires more RAM and processing power. Alternatively, connecting to cloud providers like OpenRouter or Anthropic means a Raspberry Pi 4 with just 4 GB of RAM becomes sufficient, since the heavy computational work happens in the cloud and your Pi only runs the agent's decision-making loop.

For users concerned about privacy or those in environments with unreliable internet, the local Ollama approach offers independence. For those prioritizing ease of use or running complex reasoning tasks, cloud providers offer better performance without the hardware constraints.

What Real-World Tasks Can Hermes Agent Handle?

Once installed and configured, Hermes Agent can execute a wide range of practical tasks on your Raspberry Pi. You can ask it to check system temperature, retrieve log files, manage files, or execute any shell command in plain language through your messenger app. The agent interprets your request, determines what commands or API calls are needed, executes them, and returns a human-readable summary of the results.

Because Hermes Agent maintains long-term memory across sessions, it can remember previous tasks you've asked it to perform, learn patterns in your requests, and even proactively suggest optimizations based on your usage history. This makes it genuinely useful for home automation, system monitoring, or managing a personal server over time.

The combination of Hermes Agent with Ollama represents a significant shift in how people can deploy AI locally. Rather than relying on cloud services or accepting the limitations of simple chatbots, users now have access to a self-improving AI assistant that learns from every interaction, respects privacy by running entirely on local hardware, and can be controlled from anywhere via familiar messaging apps.