Author(s): allglenn

Originally published on Towards AI.

OpenClaw vs Hermes Agent: the Honest Comparison Nobody’s Given You Yet

Peter Steinberger built the first version of what became OpenClaw in about an hour. A WhatsApp bot, a few tools bolted on, pushed to GitHub as a weekend experiment called Clawdbot. Within weeks it had 60,000 stars. By April it had overtaken React to become the most-starred repository in GitHub’s history. By early April it had passed 345,000 stars, the fastest any open-source project had ever grown to that scale.

Beyond the launch hype, the article compares OpenClaw and Hermes Agent on what matters in real use: OpenClaw’s explosive growth against a heavy security timeline of multiple high-severity CVEs and exposed instances, versus Hermes’s quieter rise with built-in command scanning and no publicly disclosed agent-specific CVEs so far. It challenges the common “stars win” narrative by showing token-processing usage where Hermes drives far more inference per deployment despite fewer installs. The piece then contrasts architecture (OpenClaw’s ecosystem/agent-fleet approach vs Hermes’s single agent that improves over time), lays out a practical migration path using the “hermes claw migrate” tool (including auditing skills, revoking credentials, and running in parallel), estimates costs tied mostly to the connected model and gateway overhead, and closes with what switchers report—OpenClaw friction from context loss and manual memory curation, Hermes friction from thinner day-one integrations—plus guidance on choosing based on whether you prefer managing security/supply-chain gaps or maturity/integration gaps.

Read the full blog for free on Medium.

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Published via Towards AI