Jiwo - Small decision models topping decision index leaderboard

Reddit r/ArtificialInteligence Models
open-source fine-tuning qwen decision-making small-language-models huggingface

Summary

A developer released Jiwo, two Qwen3.5 fine-tuned 'decision models' (a sub-1B 0.8B model and a 4B model) that topped the Decision Index leaderboard for their size categories, achieving 45.7% improvement over the best other Qwen3.5-0.8B fine-tune.

https://github.com/jiwidi/jiwo Spent the weekend turning small LLMs into decision models, with some good results and a lot of learnings along the way. Topping the decision index leaderbard for their categories https://huggingface.co/spaces/multimodalart/jev-decision-index Sharing two of them: a sub-1B model and a 4B model, both Qwen3.5 fine-tunes. When evaluated on the decision Index shared last week, the 0.8b tops the sub-1B category, 45.7% above the best other Qwen3.5-0.8B fine-tune on the leaderboard. and the 4b comes in second in the 3–6B class. Most of work was data calibration, finding external datasets and readapting them towards this scenario, so i expect a lot of improvements and work like this to come from community and push these numbers even higher. Even more if we get qwen 3.8 releases for these model categories.
Original Article

Similar Articles

Mammoth-1 and Elephant-1: frontier decision models (20 minute read)

TLDR AI

Baseten Labs release mammoth-1 (27B) and elephant-1 (9B), claiming the best decision models in the world, ranking #1 on the Jev Decision Index. The post-training of Qwen3.5 backbones uses a block-bidirectional attention mask for full attention layers and a highly scalable data recipe.

Qwen 3.6 27B on DeepSWE

Reddit r/LocalLLaMA

Qwen 3.6 27B scored 2% on the DeepSWE benchmark, placing 18/20 above Haiku 4.5 and Minimax M2.7, highlighting the gap between local and leading-edge models.