whatmodel.sh / Hormoz-8B

Hormoz-8B

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Hormoz-8B is an open-weights language model from Mann-E, released February 2025. Its published size is 8.03B parameters. Licence: mit.

Catalogue identity notes

Maker repo mann-e/Hormoz-8B @c91bcec: licence tag mit. 8,028,033,024 parameters from the Hugging Face safetensors metadata (dense, so active = total). Released 2025-02: month the maker's Hugging Face repo was created (createdAt 2025-02-01).

46.5±4.8#540 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 Hormoz-8B, out of 1132 with a score.

#modelscorewhereRAMreleased
681Mistral7B-PairRM-SPPO UCLA AGI (SPPO)47±2local~6.1GB2024-05
682EuroLLM 9B Instruct UTTER (EuroLLM)47±3local~6.9GB2024-11
683Hormoz-8B Mann-E47±5local~6.9GB2025-02
684Granite 4.0 H Micro 3B IBM47±1local~3.4GB2025-09
685GPT-3.5 Turbo (0125) OpenAI46±1api $0.75/M2024-01

see all LLMs · find the ones that fit your machine

$ what it's good at

other tests1 not in a task · 90% of its score
testresultvs the others in its rundifficultycountswhy
Open Persian LLM Leaderboard v2 average (21 tasks)53.1% ✎▂▄▂▃█▄▃▆▃▅▂▂ beats 38/81medium · avg 58%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 90%blunt · 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 Hormoz-8B · needs ~5.1 GB · from huggingface.co/mradermacher
    chat in the terminal
    llama cli -hf mradermacher/Hormoz-8B-GGUF:Q4_K_M
  3. Or start a local server and open the address it prints (http://localhost:9931)
    llama serve -hf mradermacher/Hormoz-8B-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 Hormoz-8B · needs ~5.1 GB · from huggingface.co/mradermacher

    open in LM Studio ↗

  3. Or download it in the terminal
    lms get https://huggingface.co/mradermacher/Hormoz-8B-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 Hormoz-8B · needs ~5.1 GB · from huggingface.co/mradermacher
    chat in the terminal
    ollama run hf.co/mradermacher/Hormoz-8B-GGUF:Q4_K_M

Other ways to run it

  1. Run it as published · needs ~32.11 GB · from huggingface.co/mann-e (official)
    uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='mann-e/Hormoz-8B', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"

Official weights and documentation: huggingface.co/mann-e ↗

$ how the score was worked out · Open Persian LLM Leaderboard… 90%

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
Open Persian LLM Leaderboard v2 (Part DP AI and AUT NLP Lab)1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 90%Apache-2.0
prior · pull toward the middle▇▇▇ 10%
weighted average= 46.5

$ 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