Hermes Agent
Python · MIT
An autonomous AI agent framework from NousResearch that supports multiple LLM backends and grows with user needs.
agent-frameworkautonomous-agentllmpython
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Overview
Hermes Agent vs OpenCode: two general-purpose agent frameworks
Hermes Agent (Nous Research, 224k+ stars, MIT) is a self-improving agent from Nous Research with a learning loop, autonomous skill creation, cross-session memory, and a multi-platform messaging gateway. OpenCode (SST, 192k+ stars, MIT) is a terminal-native AI coding tool focused on multi-provider support and a build / plan dual-agent design for software development. We compare positioning, model strategy, runtime model, and typical scenarios.
Projects Compared
OpenCode
TypeScript · MIT
OpenCode is an open-source terminal coding agent that supports multiple LLM providers, offering AI-powered code generation and editing in the terminal.
codingcliagenttuigo
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Feature Comparison
| Best for | Hermes Agent | OpenCode |
|---|---|---|
| Product positioning | Self-improving agent from Nous Research. Positioned around "learning loop + skill creation + cross-session memory," with a multi-platform messaging gateway (Terminal / Telegram / Discord / Slack etc.). | Terminal-native AI coding tool from SST. Positioned around "AI writes code," with built-in LSP integration and multi-provider support. |
| Model strategy | Model-agnostic: supports Nous Portal, OpenRouter, OpenAI, custom endpoints, and others. | Model-agnostic: Claude, OpenAI, Google, local Ollama, OpenRouter — no provider lock-in. |
| Extensibility | Custom agent classes, tool registration, message bus — built around "write your own agent framework." Needs Python fundamentals. | Tool allowlist plus build / plan dual-agent (plan agent is read-only), with command approval. No code required to start. |
| Runtime model | Local Python process (pip install). Multiple agents can collaborate in one process, or via message bus across processes. | Terminal TUI plus headless mode. TUI has vim-like keybindings; multiple sessions can run in parallel. |
| Best fit | Research teams that want to build / tune their own agent framework; running the Hermes open-source model family for agent experiments. | Developers who want to start today: run AI in the terminal to write code, with no Docker setup and no new framework to learn. |
GitHub Stats
| Metric | Hermes Agent | OpenCode |
|---|---|---|
| Stars | 228.5k | 195.8k |
| Forks | 44.9k | 25.1k |
| Language | Python | TypeScript |
| License | MIT | MIT |
| Last commit | August 11, 2026 | August 11, 2026 |
Which one should you choose?
Choose based on your primary workflow, language ecosystem, and integration needs. Review each project's documentation and recent GitHub activity before adopting it in production.
Frequently asked questions
Which is faster to get started with, Hermes Agent or OpenCode?
OpenCode. A terminal command plus a vim-style UI — you can run your first session in five minutes. Hermes Agent requires understanding its agent / tool / message bus abstractions, taking 30-60 minutes to run a custom agent.
Can I use Hermes models with OpenCode?
Yes. OpenCode supports the OpenAI-compatible API, and the Hermes family (Hermes-3 etc.) can be exposed via OpenRouter or self-hosted through an OpenAI-compatible proxy. This combination suits people who want to use Hermes but do not want to write their own agent framework.
How do I pick Hermes Agent versus LangChain / AutoGen?
Pick Hermes Agent if you want to run Nous Research's Hermes models with a custom agent abstraction. Pick LangChain / AutoGen if you need mature LLM-orchestration ecosystems. Hermes Agent's strength is the deep integration with its own models; its weakness is a smaller community than LangChain.
Can OpenCode run local models?
Yes. OpenCode supports local Ollama (or similar) via OpenAI-compatible APIs. A zero-cost setup is to run Ollama locally and point OpenCode at localhost.