whatmodel.sh / Hermes 3 Llama 3.2 3B

Hermes 3 Llama 3.2 3B

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Hermes 3 Llama 3.2 3B is an open-weights language model from Nous Research, released December 2024. Its published size is 3.21B parameters and a 131k-token context window. Licence: llama3.

Catalogue identity notes

Maker repo NousResearch/Hermes-3-Llama-3.2-3B @7f1a6be: licence tag llama3. 3,212,749,824 parameters from the Hugging Face safetensors metadata. Dense, so active = total. Released 2024-12: month the maker's Hugging Face repo was created (createdAt 2024-12-03). Ollama tags hermes3:3b-llama3.2-q4_K_M, hermes3:3b-llama3.2-q8_0 are the library's instruct/chat builds of this checkpoint (tag names on the pinned tags page); download sizes are estimated from the parameter count.

38.1±3.7#752 of 949 LLMsfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of Hermes 3 Llama 3.2 3B, out of 1132 with a score, then more from Nous Research.

#modelscorewhereRAMreleased
914Tulu 2 13B Allen Institute for AI38±2local~9.8GB2023-11
915Phi-3-mini-4k-instruct (Apr 2024) Microsoft38±2local~4GB2024-04
916Hermes 3 Llama 3.2 3B Nous Research38±4local~3.4GB2024-12
917Apertus 8B Instruct (2509) Swiss AI38±4local~6.3GB2025-08
918LLaMA 65B Meta38±1comparison only2023-02
more from Nous Research
534Hermes 3 Llama 3.1 405B Nous Research51±1local~114GB2024-08
585Nous Hermes 2 Yi 34B Nous Research50±7local~22GB2023-12
624Hermes 3 Llama 3.1 70B Nous Research49±1local~44GB2024-07

see all LLMs · find the ones that fit your machine

$ what it's good at

other tests1 not in a task · 94% of its score
testresultvs the others in its rundifficultycountswhy
CPTUB average (SpeakLeash, 0-5 judge scale)46.1% ✎▁▂▂▃▃█▃▆▅▄▂▃ beats 12/95easy · avg 66%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 94%at its level

$ where to run it

llama.cpp · recommended

version

  1. Install llama.cpp · Homebrew and winget installs name the commands llama-cli and llama-server instead.
    macOS / Linux
    curl -LsSf https://llama.app/install.sh | sh
    Windows
    irm https://llama.app/install.ps1 | iex

    other ways to install ↗

  2. Run Hermes 3 Llama 3.2 3B · needs ~2 GB · from huggingface.co/bartowski
    chat in the terminal
    llama cli -hf bartowski/Hermes-3-Llama-3.2-3B-GGUF:Q4_K_M
  3. Or start a local server and open the address it prints (http://localhost:9931)
    llama serve -hf bartowski/Hermes-3-Llama-3.2-3B-GGUF:Q4_K_M

LM Studio

version

  1. Install LM Studio · Open the app once before using the lms command.

    download it (macOS / Windows / Linux) ↗

  2. Run Hermes 3 Llama 3.2 3B · needs ~2 GB · from huggingface.co/bartowski

    open in LM Studio ↗

  3. Or download it in the terminal
    lms get https://huggingface.co/bartowski/Hermes-3-Llama-3.2-3B-GGUF@Q4_K_M -y
  4. Then run lms ls to see its name, and lms chat followed by that name

Ollama

version

  1. Install Ollama

    download it (macOS / Windows) ↗

    Linux
    curl -fsSL https://ollama.com/install.sh | sh
  2. Run Hermes 3 Llama 3.2 3B · needs ~2.43 GB · from ollama.com
    chat in the terminal
    ollama run hermes3:3b-llama3.2-q4_K_M

MLX (Mac)

version

  1. Install MLX (Mac) · Apple silicon Macs only, text only.
    with uv
    uv tool install mlx-lm
    or
    pip install mlx-lm
  2. Run Hermes 3 Llama 3.2 3B · needs ~1.8 GB, Mac only · from huggingface.co/mlx-community
    chat in the terminal
    mlx_lm.chat --model mlx-community/Hermes-3-Llama-3.2-3B-4bit
  3. Or start an OpenAI-compatible server at http://localhost:8080/v1
    mlx_lm.server --model mlx-community/Hermes-3-Llama-3.2-3B-4bit

Official weights and documentation: huggingface.co/NousResearch ↗

$ how the score was worked out · SpeakLeash CPTUB (Complex Pol… 94%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
SpeakLeash CPTUB (Complex Polish Text Understanding Benchmark)1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 94%MIT
prior · pull toward the middle▇▇ 6%
weighted average= 38.1

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json