whatmodel.sh / Jais Adapted 70B Chat

Jais Adapted 70B Chat is an open-weights language model from Inception (G42), released August 2024. Its published size is 69.5B parameters. Licence: apache-2.0.

Catalogue identity notes

Maker repo inception42/jais-adapted-70b-chat @07c93d6 (requested as inceptionai/jais-adapted-70b-chat, which the HF API redirects to inception42/jais-adapted-70b-chat): licence tag apache-2.0. 69,500,941,312 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).

44.5±3.7#596 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 Jais Adapted 70B Chat, out of 1132 with a score, then more from Inception (G42).

#modelscorewhereRAMreleased
749Command R Plus (04-2024) Cohere45±1local~43GB2024-04
750tulu-2-dpo-70b-ExPO Chujie Zheng (ExPO)45±2local~28GB2024-04
751Jais Adapted 70B Chat Inception (G42)45±4local~293GB2024-08
752Mistral NeMo Instruct (2407) Mistral44±1local~8.7GB2024-07
753Code-290k-6.7B-Instruct ajibawa-202344±1local~5.8GB2024-02
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▁▁▁▄▆▅▆█▆▆▆▂ #320 of 466 * · 94% of its score · 1 test

Beats Ministral 3 14B Reasoning 2512, Gemma 4 E4B, OpenThinker3 7B here, though they rank higher overall. Trails Flan-T5 XXL, LFM2 700M, EXAONE 3.5 2.4B Instruct here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
Arabic IFEval prompt-level (Inception) lab32.2% ✎▁·▁▁▂▁▄▄▆▄█▄ beats 17/38medium · avg 49%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 94%sharp · at its level

$ where to run it

Other ways to run it

  1. Run it as published · needs ~278 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-adapted-70b-chat', torch_dtype='auto', device_map='auto')('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… 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
Inception Arabic/Hindi leaderboards (AraGen-v3, HindiGen-v1, Arabic IFEval) · lab-reported1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 94%Apache-2.0
prior · pull toward the middle▇▇ 6%
weighted average= 44.5

$ improve this page

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