A 27B vision model was tasked with building canvas animations from design briefs provided as single PNG images. Six quantized versions of Qwen3.8-27B and two Bonsai variants were evaluated across three design cards using 17 objective checks per page, with results showing Opti performing competitively with Q4_K_M despite 28% smaller file size, while Bonsai struggled with JavaScript errors and token budget exhaustion.
Ternary-Bonsai-8B is a 1.58-bit quantized language model in GGUF Q2_0 format, using ternary weights ({-1, 0, +1}) with shared FP16 scales. The model ranks 2nd among compared 6B-9B parameter models despite being 1/8th their size, with implementation support in a custom llama.cpp fork.