Model Releases
Question: UkisAI Swift Ternary Bonsai 2 27B?
Hey community, Jovan from UkisAI here, We're the team behind Swift Qwen3.8 27B, the Qwen model with token usage and overthinking error improvements Our estimate is that we can make a great improvement
Hey community, Jovan from UkisAI here, We're the team behind Swift Qwen3.8 27B, the Qwen model with token usage and overthinking error improvements Our estimate is that we can make a great improvement to Bonsai 2, as our testing indicates that it suffers greatly from overthinking loops and in general high token usage impacting it's performance. My ask for you is: Is a Swifted version of Bonsai 2 something you guys would enjoy? If yes, what size is the most relevant. 1-bit, 2-bit or both? Thank you for the amazing feedback on Swift. We are glad you are enjoying it. Our download count jumped from 100k -> 150k overnight (community quants included). For context, this is our model: https://www.reddit.com/r/LocalLLaMA/s/iCIbhxO8ue https://huggingface.co/ukisai/Swift-Qwen3.8-27B-GGUF submitted by /u/Secure_Recording_472 [link] [comments]
Related
- Thank you :) Swift Qwen 3.8 27B now has 100k+ downloads, is #1 finetune and #9 model on HuggingFace Trending
- Qwen 3.8 27B Overthinking, It has to be done, it has to be overthinking to punch Opus 4.6
- Cut Qwen3.8-27B Reasoning Tokens by 40% -- 3.8 'ThinkingCap' benchmarked!
- UkisAI Swift-Qwen3.8-27B / -58.3% thinking, x1.95 speed while keeping the accuracy of xhigh
- ~22% less weight VRAM, lossless: base-3 packing for ternary GGUFs
Source: r/LocalLLaMA | 2026-09-18