OpenClaw vs Hermes Agent (2026): Which AI Agent Should You Run?

Key Takeaways

• Hermes recently passed OpenClaw in daily token volume (~224B vs ~186B tokens/day). OpenClaw is the more mature project (released Nov 2025, 137+ releases, ~5,400 skills); Hermes is newer (Feb 2026, ~11 releases) but growing fast.
• Both are the same shape: an LLM wrapped with tools (MCP servers), skills (markdown workflow files), memory, and a gateway (Telegram, Discord, email). What differs is how well each part works, not what they can theoretically do.
• OpenClaw is skill-catalog-driven: browse Claw Hub (5,400+ skills), click install. Custom skills exist but you must ask the model to build each one manually.
• Hermes is a self-learning loop: its "curator" watches your sessions, auto-detects a workflow you've repeated several times, and writes a skill for it in the background — then moves skills through active → stale → archived states so they don't pile up as context bloat.
• Memory: Hermes writes to memory more intelligently and recalls across more of it; OpenClaw's memory works but is less efficient and less automatic. This is why Hermes gets cheaper to run over time — it reuses saved skills instead of re-discovering the same workflow.
• OpenClaw's remaining edge is the gateway layer: it's easier to wire up multiple gateways (Telegram, Discord, WhatsApp, Line, web widget) routed into shared-memory agents — better for customer-facing or multi-user setups. Its control board is more configurable but more complex; Hermes' UI is more bare-bones but works out of the box.
• Security: OpenClaw's larger skill ecosystem is a bigger attack surface (the Feb 2026 incident exposed 40,000+ instances). Hermes pulls in less external code, so its surface is smaller. Both are best run on a disposable VPS you can nuke — not your own machine.
• Verdict: pick Hermes for a personal daily driver you chat with a lot and want to improve over time; pick OpenClaw for advanced, multi-channel, customer-facing deployments where you want maximum control.