HauhauCS has released two new uncensored, balanced versions of the Gemma 4 models: Gemma4-26B-A4B and Gemma4-31B-QAT. Both variants incorporate Multi-Token Prediction (MTP) draft heads to enable speculative decoding, resulting in significant inference speed improvements. The 26B-A4B model achieves approximately a 35% speed boost, while the 31B model sees a 53% increase, with identical output quality verified by the model's drafting mechanism. These releases utilize QAT-aware quantization, making Q4_K_M the optimal format as higher precision offers no quality gains for these specific models. The 26B-A4B is a Mixture of Experts architecture with roughly 4 billion active parameters per token, whereas the 31B variant is a dense model offering higher capability for users with sufficient VRAM. Both models include vision support via mmproj files and maintain a 262K context window. The author notes that GenRM testing resulted in zero refusals across 465 prompts, confirming their uncensored nature.