Hermes hosting

Nous Research’s Hermes models, served privately behind your own API.

LLM runtimesModel weights under their own terms; server MITfrom $16.99/mo
In short

Hermes hosting at AIHostBox means a dedicated, single-tenant Hermes instance on our infrastructure: we install it, pin it to a reviewed release, put it behind TLS on your domain, back it up nightly and keep it patched. Plans start at $16.99 per month and the admin account, the data and any API keys are yours.

OpenAI-compatibleSteerableFunction callingQuantized GGUF

Hermes is a family of open-weight models from Nous Research, built by fine-tuning strong base models rather than training from scratch. Hermes 3 8B sits on Meta’s Llama 3.1 8B; Hermes 4 14B sits on Qwen3 14B. Both use the ChatML prompt format and a documented tool-calling convention, where the model returns function calls as JSON inside tool_call tags. That consistency is why agent frameworks and roleplay front-ends often ship presets for Hermes specifically.

Hermes 4 adds hybrid reasoning: it can think inside explicit think tags before answering, or answer directly, depending on how you prompt it. On a laptop the model competes with everything else for memory and stops when the lid closes. On a server it becomes a fixed endpoint that several tools can share, with its weights, logs and prompts kept on hardware you rent rather than on a third party’s inference service.

Hermes hosting plans

StarterRuns 7-8B models (Q4)
8 GB RAM · 4 vCPU · NVMe
$16.99/mo
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PlusRuns 13B models (Q4)
12 GB RAM · 6 vCPU · NVMe
$27.99/mo
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Every plan is a dedicated single-tenant instance with NVMe storage, nightly off-box backups, TLS and managed patching. Quarterly, semi-annual and annual terms are discounted at checkout. Model tokens are not included — you bring your own key.

How we run Hermes

One GGUF inference server loaded with a quantized Hermes build, exposing an OpenAI-compatible /v1 chat completions API on your domain with an API key.

What we configure for you

  • Model file chosen for your plan: Hermes 3 Llama 3.1 8B or Hermes 4 14B at Q4
  • ChatML chat template so system prompts and tool calls are formatted as Nous documents them
  • Context length and thread count matched to your dedicated cores and RAM
  • Sampling defaults from the model card (Hermes 4: temperature 0.6, top_p 0.95, top_k 20)
  • API key on the endpoint and TLS on your own subdomain

Which plan fits

Starter (8 GB, 4 vCPU) is the plan for Hermes 3 8B and gives roughly 5-15 tokens/s at Q4, which is fine for chat and background agents. Plus (12 GB, 6 vCPU) is needed for Hermes 4 14B; it fits comfortably but generates noticeably slower than the 8B.

The honest limits

This is CPU inference: long reasoning traces and many concurrent users will queue. The larger Hermes 4 models (70B, 405B) are out of reach without a GPU plan.

What people run Hermes for

Agent backbone

A model that respects a long system prompt without drifting.

Private assistant

Run the model behind your own endpoint with no third-party logging.

Tool-calling experiments

Test function calling against a model whose tool format is published and stable.

Character and roleplay back-end

Serve a steerable model to a front-end such as SillyTavern over the private network.

Licence and version policy

ItemPosition
Upstream licenceModel weights under their own terms; server MIT
Sold as managed hostingYes
TenancySingle tenant — one customer per instance
PatchingCritical advisories within 24 hours, high severity within 72

Our full position on licences, including the applications we decline to sell, is on the licensing page.

Works well with Hermes

More LLM runtimes we host

Questions

Hermes hosting: your questions

Which Hermes version do you run?
We deploy the current stable Hermes release in a quantized GGUF build sized to your plan; tell us if you need a specific version pinned.
Is it as fast as a GPU?
No. Expect the same CPU throughput as our other runtime plans — good for chat and background work, not for realtime products.
Which Hermes models fit on each plan?
Starter (8 GB) runs Hermes 3 Llama 3.1 8B at Q4 with room for a working context. Plus (12 GB) runs Hermes 4 14B at Q4. The 70B and 405B Hermes 4 builds need far more memory than any CPU plan we sell, so we do not offer them.
Does tool calling work through the API?
Hermes emits tool calls as JSON inside tool_call tags. Frameworks that know the Hermes format parse these directly, and the Hermes 4 model card names the hermes tool parser for vLLM. Test your own framework against the endpoint before relying on it in production, because parsers differ in how strictly they read the tags.
Can I turn Hermes 4’s reasoning on and off?
Yes. Hermes 4 reasons inside think tags when asked to, either through the chat template’s thinking flag or a system prompt, and answers directly otherwise. On CPU, reasoning mode costs real time because every thinking token is generated before the answer starts, so leave it off for quick chat.
What licence do the weights carry?
It depends on the model. Hermes 4 14B is published under Apache-2.0. Hermes 3 8B inherits Meta’s Llama 3 community licence, which has its own acceptable-use terms and a clause for very large services. The serving software we run is MIT-licensed; the model terms are yours to comply with.

Run Hermes without running a server

A dedicated Hermes instance, deployed and maintained by us. Month to month, cancel whenever.