whatmodel.sh / PLLuM-12B-nc-instruct (2507)

PLLuM-12B-nc-instruct (2507) is an open-weights language model from PLLuM consortium (CYFRAGOVPL), released July 2025. Its published size is 12.25B parameters. Licence: other (pllum-1.0).

Catalogue identity notes

Maker repo CYFRAGOVPL/PLLuM-12b-nc-instruct-2507 @50be19b (requested as CYFRAGOVPL/pllum-12b-nc-instruct-250715, which the HF API redirects to CYFRAGOVPL/PLLuM-12b-nc-instruct-2507): licence tag other (pllum-1.0). 12,247,802,880 parameters from the Hugging Face safetensors metadata (dense, so active = total). Released 2025-07: month the maker's Hugging Face repo was created (createdAt 2025-07-23). Gated repository (licence acceptance required on Hugging Face).

50.3±3.9#431 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 PLLuM-12B-nc-instruct (2507), out of 1132 with a score, then more from PLLuM consortium (CYFRAGOVPL).

#modelscorewhereRAMreleased
559Infinity-Instruct-7M-Gen-mistral-7B BAAI50±2local~6.1GB2024-07
560Jamba 1.5 Large AI21 Labs50±1local~839GB2024-08
561PLLuM-12B-nc-instruct (2507) PLLuM consortium (CYFRAGOVPL)50±4local~27GB2025-07
562Mistral-NeMo-Minitron 8B Instruct NVIDIA50±8local~6.9GB2024-10
563Gemini 1.5 Flash (001) Google50±1comparison only2024-05
more from PLLuM consortium (CYFRAGOVPL)
423PLLuM-12B-nc-chat (2507) PLLuM consortium (CYFRAGOVPL)55±4local~27GB2025-07
474Llama-PLLuM-70B-instruct (2412) PLLuM consortium (CYFRAGOVPL)53±3local~29GB2025-02
484Llama-PLLuM-70B-chat (2412) PLLuM consortium (CYFRAGOVPL)53±4local~29GB2025-02

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$ what it's good at

other tests1 not in a task · 93% of its score
testresultvs the others in its rundifficultycountswhy
CPTUB average (SpeakLeash, 0-5 judge scale)66.5% ✎▁▂▂▂▃█▃▆▅▄▂▃ beats 47/95easy · avg 66%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 93%at its level

$ where to run it

Other ways to run it

  1. Run it as published · needs ~24.5 GB · from huggingface.co/CYFRAGOVPL
    uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='CYFRAGOVPL/PLLuM-12b-nc-instruct-2507', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])"

Weights and documentation: huggingface.co/CYFRAGOVPL ↗

$ how the score was worked out · SpeakLeash CPTUB (Complex Pol… 93%

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▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 93%MIT
prior · pull toward the middle▇▇ 7%
weighted average= 50.3

$ improve this page

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data updated · sources and licences · json