Gemma 4 vs Qwen3.5 on SVG style

A viral community benchmark is challenging assumptions about the coding and creative capabilities of leading open-weight AI models. User u/iChrist conducted a direct comparison between Google's recently released Gemma 4-31B and Alibaba's Qwen3.5-27B, running both models with Q4 quantization through the Unsloth optimization framework. The results revealed a significant and unexpected strength for Gemma 4, which not only met but exceeded expectations in technical domains beyond its advertised specialties.

While Gemma 4 was anticipated to excel in creative writing and translating obscure languages—areas where its predecessor showed promise—the test demonstrated superior performance in function calling (AI's ability to execute code-based tasks) and general coding. Most notably, Gemma 4 outperformed Qwen3.5 in generating Scalable Vector Graphics (SVG), a format requiring precise, structured code to create visual elements. This finding is particularly impactful for developers and designers seeking AI assistance for technical creative work. The benchmark has sparked discussion within the AI community, with users now investigating potential areas, such as reasoning or specific coding libraries, where the highly-regarded Qwen3.5 model might still hold an advantage.