whatmodel.sh / Jais Family 6p7b (6.7B) Chat

Jais Family 6p7b (6.7B) Chat

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Jais Family 6p7b (6.7B) Chat is an open-weights language model from Inception (G42), released August 2024. Its published size is 7.14B parameters. Licence: apache-2.0.

Catalogue identity notes

Maker repo inception42/jais-family-6p7b-chat @683805e (requested as inceptionai/jais-family-6p7b-chat, which the HF API redirects to inception42/jais-family-6p7b-chat): licence tag apache-2.0. 7,142,689,824 parameters from the Hugging Face safetensors metadata (dense, so active = total). Released 2024-08: month the maker's Hugging Face repo was created (createdAt 2024-08-02). Gated repository (licence acceptance required on Hugging Face).

42.1±3.2#666 of 949 LLMsfrom 2 benchmark results across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of Jais Family 6p7b (6.7B) Chat, out of 1132 with a score, then more from Inception (G42).

#modelscorewhereRAMreleased
823Yi-1.5 9B (base) 01.AI42±2local~6.8GB2024-05
824LWM-Text-Chat-1M Large World Model (UC Berkeley)42±5local~5.8GB2024-02
825Jais Family 6p7b (6.7B) Chat Inception (G42)42±3local~32GB2024-08
826SILMA 9B Instruct v1.0 SILMA AI42±3local~7.6GB2024-08
827Claude Instant 1.2 Anthropic42±1comparison only2023-08
more from Inception (G42)
323Jais 2 70B Chat Inception (G42)59±4comparison only2025-12
537Jais 2 8B Chat Inception (G42)51±5comparison only2025-12
713Jais Family 30B 16K Chat Inception (G42)46±3local~131GB2024-08

see all LLMs · find the ones that fit your machine

$ what it's good at

chat & writing▁▁▁▄▆▅▆█▆▆▆▂ #346 of 466 * · 65% of its score · 1 test

Beats Ministral 3 14B Reasoning 2512, Gemma 4 E4B, OpenThinker3 7B here, though they rank higher overall. Trails LFM2 350M, Flan-T5 XXL, LFM2 700M here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Arabic IFEval prompt-level (Inception) lab22.5% ✎▁·▁▁▂▁▄▄▆▄█▄ beats 13/38medium · avg 49%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 65%sharp · at its level
other tests1 not in a task · 30% of its score
testresultvs the others in its rundifficultycountswhy
AraGen-v3 3C3H score (Inception, Claude Sonnet 4 judge) lab21.3% ✎▁▁·▁▂▂▄█▄▅▄▄ beats 16/66hard · avg 31%▇▇▇▇▇▇▇▇▇▇▇▇ 30%typical

$ where to run it

Other ways to run it

  1. Run it as published · needs ~28.57 GB · from huggingface.co/inception42 (official)
    uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='inception42/jais-family-6p7b-chat', torch_dtype='auto', device_map='auto', trust_remote_code=True)('Once upon a time', max_new_tokens=40)[0]['generated_text'])"

Official weights and documentation: huggingface.co/inception42 ↗

$ how the score was worked out · Inception Arabic/Hindi leader… 95%

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
Inception Arabic/Hindi leaderboards (AraGen-v3, HindiGen-v1, Arabic IFEval) · lab-reported2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%Apache-2.0
prior · pull toward the middle▇ 5%
weighted average= 42.1

$ 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