OpenCLAW vs Hermes

I run [OpenCLAW][1]. [Hermes][2] is the open-source [harness][6] most CEOs are asking me about. Here is how the two differ, what each one is good at, and the one place where Hermes pulls clearly ahead.

The same question lands in my inbox most weeks, and has for a couple of months now: "Should I install OpenCLAW or Hermes?" The CEOs asking have read the explainers. They understand both. They just want me to weigh in before they commit a weekend to one of them.

Here is what I tell them. The honest answer is that the two harnesses solve the same problem with different operating models, and the right pick depends on three things about how you actually work. Only one of those three has a clear winner. The other two are preferences. Below: the scan-version table, the axes that differ, the one place where Hermes wins outright, and a five-minute decision framework.

The scan version

The three rows that move the decision are Primary interface, Model backends, and Operator's manual. The rest is texture.

What is the same on both

Before the differences, the parts that do not differ.

Both solve the same problem. The CEO automation gap is memory + connectors + [skills][3] + routines, on top of a model. Both harnesses solve all four. The differences are in how the operator interacts with the solution, not in whether the solution exists.

Skills are portable. Both read the open agentskills.io SKILL.md standard. A skill folder you write today works on either harness, and on Claude Code too. Skills are the operator's investment; the model is rented. The lock-in risk on the skills layer is low whichever harness you pick.

The model is interchangeable. Both work with multiple LLMs. Both let you swap the backend if Anthropic ships something new, or if OpenAI does, or if the next-best model comes from somewhere else.

Most workflows transfer. A Monday brief, a CRM hygiene scan, a pre-meeting prep, a Friday investor update. These can be written on either harness with minor reframing. If you change your mind in six months, your workflows come with you.

Both sit a layer above the terminal. Each one is the harness you reach for once the terminal habit is in place. If you have not made that move yet, [why CEOs should use Claude Code in the terminal][4] is the place to start; the harness question is the one after that.

The axes that actually differ

Five differences worth weighing. Take them one at a time.

Where the harness lives

OpenCLAW is laptop-resident. You type a command in the folder where your work lives and the harness runs on the machine on your desk. Hermes is designed to live on a [cloud VM][9] so the Telegram-first interface has a 24/7 endpoint to receive your messages.

Both can be reached from a phone. OpenCLAW reaches the phone through a thin web UI or a remote login to the cloud VM you set up. Hermes was built phone-first from the ground up. If your work happens at a desk, the OpenCLAW pattern matches your day. If your work happens between meetings, in transit, or on weekend mornings before the kids are up, the Hermes pattern matches yours.

Preference, not verdict.

Ecosystem maturity

OpenCLAW has been public about six months longer than Hermes and has accumulated a larger library of skills, connectors, and operator-published workflows. The community is the moat that compounds. For a CEO who values lift-and-shift over write-your-own, that delta is the difference between a weekend of installation and a quarter of it.

Hermes is younger. Some features the OpenCLAW ecosystem has had for a quarter are still maturing on the Hermes side. Operators willing to write their own skills will be fine on either; operators who want pre-built connectors will find more options in the OpenCLAW catalog today.

Memory architecture

OpenCLAW uses a tiered set of memory files: a top-level brief the agent reads on every session, plus narrower memory files per skill or domain. The architecture is paper-readable. You can open the files in any text editor and see what the agent knows.

Hermes uses a local [SQLite database][8] with full-text search. The agent recalls context across sessions by querying its own database, rather than re-reading memory files in full each session. Both architectures work. The OpenCLAW model rewards operators who want to read and edit what the agent remembers in plain text; the Hermes model rewards operators who want recall to be implicit and search-driven.

Model backends and the Grok question

This is the axis where Hermes has a clear edge for some CEOs.

Both harnesses are model-agnostic. Both work with Anthropic, OpenAI, and OpenRouter. The May 2026 xAI integration on Hermes added something neither competitor offers natively: the ability to burn X Premium Grok credits as the model backend instead of paying API rates. For a CEO already paying for X Premium, the marginal cost of running an agent through Grok approaches zero.

The trade-off is model quality. For CEO-grade tasks (writing, analysis, judgment, long-context synthesis), Anthropic models still produce stronger output than Grok 4.x. Use Grok where the cost story matters most: high-volume, low-stakes, repetitive work. Use Claude where the quality story matters: anything that goes to a customer, a board, or a court.

Grok does have one specific edge worth naming. It has superior knowledge of current events from the last week or so, which is genuinely useful for any workflow that needs real-time awareness. Mix-and-match the model to the task; do not pick one and stop thinking.

If high-volume agent traffic is part of your plan and X Premium is already a sunk cost, the Hermes/Grok combination is real money saved per year. If you are not cost-sensitive at the leverage layer, this axis does not move the decision.

Governance and what stewards each project

OpenCLAW is stewarded by a non-profit foundation. The creator, Peter Steinberger, now works at OpenAI; the foundation runs the project independent of any single company. The license is open-source. No single company controls OpenCLAW.

Hermes is built by Nous Research, MIT-licensed. Active development, weekly releases, healthy community on X.

Both are open-source. Both have active maintainers. The governance shapes are slightly different (foundation vs research lab) but for the CEO running one of them, the day-to-day implication is the same. You can read the code. You can fork it. The project is not going away.

When Hermes is the right pick

One axis has a clear answer rather than a preference. If you run high-volume agent traffic, are cost-sensitive at the model layer, and already pay for X Premium, the Hermes/Grok combination saves you real money. For a CEO running heavy agent traffic per day, the difference between burning Grok credits and paying Anthropic API rates compounds into thousands of dollars a year, with the quality caveat above.

A second softer pull toward Hermes: if your work day happens primarily on your phone and a laptop terminal feels like the wrong tool for how you actually work, the Telegram-first pattern is genuinely better for that operator pattern.

Neither of these is a knock on OpenCLAW. They are honest carve-outs where the cheaper or more-mobile harness is the better fit for a specific operator.

A 5-minute decision framework

Three questions. Answer them honestly and the right harness is usually obvious by the end.

1. Where do you want your harness to live: laptop or phone? If phone, lean Hermes. If laptop, lean OpenCLAW. If you do not have a strong preference, lean toward whichever fits how you actually work today, not how you wish you worked.

2. How much off-the-shelf ecosystem do you need? If you want to lift-and-shift pre-built connectors and skills for the systems your business runs on (CRM, inbox, file storage, Slack), the larger OpenCLAW ecosystem matters more. If you are writing your own from scratch anyway, the ecosystem delta matters less.

3. Does the Grok-via-X-Premium cost story matter to you? If you are cost-sensitive at the leverage layer and already pay for X Premium, that single feature is worth real money. If you are not cost-sensitive at the leverage layer, treat this axis as a tie.

If all three answers point at the same harness, install it this weekend. If they are split, the tiebreak is whichever community you want to be part of for the next twelve months.

Do this next

Two paths, depending on which way you went.

If you are going with OpenCLAW. The deep operator's manual is [The Complete Guide to OpenCLAW for CEOs][7]. 270 pages. $99. The exact 90-day rollout I walked myself, with the workflows, memory tiers, and skill scaffolds laid out as you would actually install them.

If you are going with Hermes. Start with the [Nous Research repo][10] and the install instructions on the project's GitHub page. The X discourse around Hermes is unusually active; the operator patterns coming out of it are worth reading before you wire anything in.

Either way: tell me what you wired first. I love seeing what people pick and what earns its keep in the first week.

[1]: /articles/what-is-openclaw [2]: /articles/what-is-hermes [3]: /articles/what-are-skills-in-claude-code [4]: /blog/why-ceos-claude-code-terminal [5]: https://agentskills.io [6]: /articles/what-is-a-harness [7]: /ceo-guide-for-openclaw [8]: /articles/what-is-a-sqlite-database [9]: /articles/what-is-a-cloud-vm [10]: https://github.com/NousResearch/hermes-agent