Hermes Agent runs comfortably on modest hardware for chat-only workloads, but the browser toolset and large model contexts push memory and disk fast. Here's the minimum, the recommended, and where the bottlenecks actually are in 2026.
At a Glance
| Minimum | Recommended | |
|---|---|---|
| RAM | 1 GB | 2–4 GB |
| CPU | 1 vCPU | 2 vCPU |
| Disk | 2 GB | 10 GB+ (with browser toolset) |
| Python | 3.11 | 3.12 or 3.13 |
| Node.js | Installed for you — only the browser toolset uses it | |
| OS | Linux / macOS / Windows / WSL2 | Linux x86_64 or arm64 |
| GPU | None | None (models are remote) |
| Network | Outbound 443 | Outbound 443 + inbound for webhooks |
RAM
We host Hermes Agent, so rather than estimate, we measured. Across 31 live Hermes containers on our fleet, resident memory came in at a median of 282 MB, with a minimum of 139 MB and a maximum of 858 MB. Those are real resident figures, not values clamped by a container limit — the containers are capped at 2–4 GB and nothing was close to its ceiling.
The number that matters for sizing is the peak, not the median. A container caught mid-response — actually generating, tools running — touched 1.1 GB. That is the figure to size against, because it is what your box has to absorb on a busy turn. Large context windows (Claude 200k, Gemini 1M) push the working set up transiently in the same way.
A separate browser container adds only 8–95 MB at idle, which is far less than people expect — the cost of the browser toolset is mostly disk and burst, not steady-state memory.
For a single-user VPS, 2 GB is comfortable. For multi-user managed hosting, plan on ~1 GB per concurrent active container.
Worth knowing before you over-buy: the browser toolset is not on by default. It ships as a core toolset but stays inactive until you add browser to toolsets in your config. So the higher numbers on this page are a ceiling you opt into, not the baseline you start from — a stock install sizes against the chat-only figures.
CPU
Hermes Agent is mostly I/O bound — it waits on model responses, network webhooks, and disk reads. 1 vCPU is enough for low-volume use; 2 vCPU helps when the browser toolset is rendering pages or skills do CPU-heavy parsing (PDF, video).
Measured on the same 31 containers: an idle Hermes agent sits at 0.2–0.7% CPU. It is doing essentially nothing while it waits. But a container actively generating a response was caught at over 100% — a full core saturated. That gap is the whole story of sizing Hermes: idle cost is close to zero, so what you are really buying is headroom for concurrent bursts. One agent that is busy 5% of the time and 20 idle agents cost about the same.
Disk
The base install is small (under 500 MB), but the workspace at ~/.hermes grows with chat history, embeddings, and any files your agent touches. Enabling the browser toolset pulls a full Playwright Chromium plus per-session profile data, which is the single biggest jump in disk use. For reference, the official multi-arch Docker image is roughly 900 MB compressed before any of your data. Plan on:
- 2 GB — minimum, chat-only, ephemeral workspace
- 10 GB — comfortable for browser toolset + memory store
- 20 GB+ — if you keep long chat history and large skill data
Python Version (Not Node.js)
Hermes Agent is a Python project, and this trips people up constantly because so much of the agent ecosystem is Node. The requirement is Python 3.11 or newer, below 3.14 — the upper bound exists because Rust-backed dependencies like pydantic-core don't ship wheels for 3.14 yet.
You mostly don't install Python yourself. The official installer provisions it through uv without sudo, so a clean box needs no manual Python setup at all.
Node.js does get installed — the installer bundles v22, and the official Docker image builds on Node 26 — but it is a secondary dependency, not a version you choose. It exists to run the browser automation (agent-browser, resolved via npx on first use) and the WhatsApp bridge. If you never enable the browser toolset, Node sits unused. So "what Node version does Hermes need?" is the wrong question to size a box around; Python is the runtime that matters.
OS Support
- Linux — first-class, x86_64 and arm64
- macOS — Intel and Apple Silicon, dev environments only
- Windows — natively, via the PowerShell installer; WSL2 also works
- Docker — the official image works on any OS that runs Docker
GPU? No.
Hermes Agent does not run local model inference. Model calls go to remote providers (OpenRouter, Anthropic, OpenAI, etc.) over HTTPS. You do not need a GPU. If you want local inference, point Hermes at a local Ollama or LM Studio endpoint — the GPU lives on the inference server, not the Hermes box.
Network
- Outbound 443 to your model provider (required)
- Inbound 80/443 if you accept channel webhooks (Telegram, Slack, etc.)
- Outbound to ClawHub / skill registries if installing skills at runtime
Sizing Cheat Sheet
- Personal bot, chat-only: 1 vCPU / 1 GB RAM / 5 GB disk — any $4–5/mo VPS
- Personal bot + browser toolset: 1 vCPU / 2 GB RAM / 10 GB disk
- Team bot, 5–10 concurrent users: 2 vCPU / 4 GB RAM / 20 GB disk
- Production, 50+ concurrent: 4 vCPU / 8 GB RAM / dedicated node
Skip the Sizing
OpenClaw Launch hosts Hermes Agent on right-sized containers with the browser toolset, memory store, and channel webhooks pre-wired. Plans from $3/mo.
Originally published at openclawlaunch.com.
Top comments (0)