Hermes Glossary
Hermes is a family of post-trained open-weight language models produced by Nous Research. Nous takes existing base models and trains them for instruction following, steerability, structured output, reasoning, and tool use.
Hermes is a family name rather than one fixed architecture. Hermes 4 includes a 14-billion-parameter model based on Qwen 3 and 70-billion- and 405-billion-parameter models based on Llama 3.1. Hermes 4.3 added a 36-billion-parameter model based on ByteDance Seed. Older Hermes releases used other bases, including Mistral. The name therefore tells you mainly about Nous’s post-training approach; the model card still matters for architecture, licence, hardware needs, prompt format, and supported tools.
For local use, operators usually download official weights or community quantisations from Hugging Face and run them through software such as LM Studio or Ollama. A small quantised release may fit on a laptop; a 70B or 405B model requires much more memory and, at useful speeds, usually server-class hardware. The runner, quantisation, context length, and model variant all affect the result.
Hermes remains relevant to the Dictionary’s Sovereign Compute argument because it offers inspectable weights and local deployment choices. It should be treated as one candidate family, not as a timeless default. Local-model recommendations age quickly and should be tested against the operator’s actual hardware and work.
Sources
- Nous Research, Hermes 4 collection.
- Nous Research, Hermes 4 — Qwen 3 14B model card.
- Nous Research, Hermes 4.3 36B model card.
See also
- Nous Research — the producer
- Sovereign Compute
- Llama and Qwen — base-model families used by Hermes 4
- LM Studio and Ollama — local runners