whatmodel.sh / Jais 2 8B Chat

Jais 2 8B Chat is an open-weights language model from Inception (G42), released December 2025. Its published size is 8.09B parameters. Licence: apache-2.0.

Catalogue identity notes

Maker repo inception42/Jais-2-8B-Chat @da0e163 (requested as inceptionai/Jais-2-8B-Chat, which the HF API redirects to inception42/Jais-2-8B-Chat): licence tag apache-2.0. 8,090,401,280 parameters from the Hugging Face safetensors metadata (dense, so active = total). Released 2025-12: month the maker's Hugging Face repo was created (createdAt 2025-12-09). Comparison-only here: no run command was verified for this checkpoint (architecture Jais2ForCausalLM, model_type 'jais2', ships no custom code; transformers support for it was not verified here). Gated repository (licence acceptance required on Hugging Face).

51.2±4.6comparison only: no current run option verifiedfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of Jais 2 8B Chat, out of 1132 with a score, then more from Inception (G42).

#modelscorewhereRAMreleased
535GPT-4 (0613) OpenAI51±1api $37.50/M2023-06
536OpenCoder-8B-Instruct INF (infly)51±1local~6.4GB2024-11
537Jais 2 8B Chat Inception (G42)51±5comparison only2025-12
538Command A Translate (08-2025) Cohere51±5api price unknown2025-08
539xLAM-2-1b-fc-r Salesforce51±4local~2.6GB2025-03
more from Inception (G42)
323Jais 2 70B Chat Inception (G42)59±4comparison only2025-12
713Jais Family 30B 16K Chat Inception (G42)46±3local~131GB2024-08
727Jais Family 30B 8K Chat Inception (G42)45±3local~131GB2024-08

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$ what it's good at

other tests1 not in a task · 91% of its score
testresultvs the others in its rundifficultycountswhy
AraGen-v3 3C3H score (Inception, Claude Sonnet 4 judge) lab34.0% ✎▁▁·▁▂▂▄█▄▅▄▄ beats 32/66hard · avg 31%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 91%at its level

$ where to run it

No verified API or download recorded yet · add one

Official weights and documentation: huggingface.co/inception42 ↗

$ how the score was worked out · Inception Arabic/Hindi leader… 91%

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▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 91%Apache-2.0
prior · pull toward the middle▇▇▇ 9%
weighted average= 51.2

$ improve this page

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data updated · sources and licences · json