# Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced by HauhauCS Source: https://savrn.com/models/gemma4-12b-qat-uncensored-hauhaucs-balanced Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Model Card Gemma4-12B (QAT) uncensored by HauhauCS. 0/465 Refusals No changes to datasets or capabilities — fully functional, 100% of what the original authors intended, just without the refusals. Built from the official QAT weights, so the 4-bit quant stays close to full-precision quality. The Balanced variant (recommended — 99%+ of users will be happy here) uses optimized full uncensoring tuned especially for agentic coding, reasoning, creative writing and reliability-critical tasks. It reasons before answering and stays dependable and on-instruction. An Aggressive variant, for cases where Balanced still deflects too much, after current testing is not required. Ships with an MTP… Excerpt from the card by HauhauCS, licensed gemma. ## Identity and Version Repository HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced Publisher HauhauCS Task Image and text to text Modality Image and text Library Not stated by the source Parameters Not stated by the source Languages en Revision ae8045ac2bd216293ca49a3065da2c942dde4b68 First published 2026-06-22 Last updated 2026-06-25 ## Files and Weights 5 files, 7.8 GB in total. The weights are 3 files totalling 7.8 GB in gguf. Weights3 files · 7.8 GB Documentation1 file · 3.8 KB Repository1 file · 1.8 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf | Weights | 7.4 GB | 59656d7494d6 | | mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf | Weights | 175.1 MB | b59e815479b7 | | mtp-gemma-4-12B-it.gguf | Weights | 253.7 MB | c50c91c35f04 | | README.md | Documentation | 3.8 KB | — | | .gitattributes | Repository | 1.8 KB | — | ## License and Download License gemma Access Open weights, no gate Download size 7.8 GB [Download from HauhauCS](https://huggingface.co/HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced) Released by HauhauCS through its official repository on Hugging Face. ## Built From - Derived from [google/gemma-4-12B-it](https://savrn.com/models/gemma-4-12b-it) - Quantized from [google/gemma-4-12B-it](https://savrn.com/models/gemma-4-12b-it) ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 7.8 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced ### Can I use Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced commercially? Yes, with conditions. Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced is released under Gemma Terms of Use. Gemma models are released under Google's Gemma Terms of Use, which permit commercial use and redistribution subject to the Gemma Prohibited Use Policy, whose restrictions must be passed on to anyone the model is distributed to. ## Similar Models Model · Image and text to text ### [Qwen3.8-Flash-Next-GSQ-RCO-GGUF](https://savrn.com/models/qwen3-8-flash-next-gsq-rco-gguf) [IST Austria Distributed Algorithms and Systems Lab](https://savrn.com/model-publishers/ista-daslab) Non-uniform GGUF quantizations of a 512-expert MoE, produced with GSQ and RCO, with a vision projector for multimodal use. This repository provides GGUF quantizations of Qwen3.8-Flash-Next at four sizes, together with the model's vision projector (mmproj) for multimodal use. In contrast to uniform quantization, which applies a single quantization type to all weight tensors, each model here assigns a separate quantization type to every tensor. The assignment is obtained by a gradient-based search that allocates precision according to per-tensor sensitivity, subject to a total size budget. The resulting files are standard GGUF and run unmodified in llama.cpp, Ollama, and LM Studio. A… Open weights apache-2.0 gguf [View model](https://savrn.com/models/qwen3-8-flash-next-gsq-rco-gguf) Model · Image and text to text ### [Qwen3.8-27B-iMatrix-NVFP4-MTP-GGUF](https://savrn.com/models/qwen3-8-27b-imatrix-nvfp4-mtp-gguf) [Michał Piszczek](https://savrn.com/model-publishers/cdiamond) I built this quant because the ready-made FP4 file answered the wrong question. It was fast, but on my short WikiText-2 control it scored 6.4949 PPL. Plain Q40 scored 6.3798. The first higher-quality hybrid went too far the other way: good perplexity, 34.19 tok/s, and no comfortable room for 256K plus vision. This is the build that survived both gates. It is a 17.1 GB, 5.01 BPW mixed-precision GGUF of Qwen/Qwen3.8-27B. It keeps large, tolerant matrices in native NVFP4 and spends more bits on selected attention, Gated DeltaNet, and late FFN tensors. The trained MTP layer remains embedded in the same GGUF. This is not a fine-tune. I built the private calibration workload from 5,472 messages… Open weights apache-2.0 [View model](https://savrn.com/models/qwen3-8-27b-imatrix-nvfp4-mtp-gguf) Model · Image and text to text ### [Qwen3.8-27B-GGUF](https://savrn.com/models/qwen3-8-27b-gguf-3) [GGML Org](https://savrn.com/model-publishers/ggml-org) Run with https://llama.app - https://huggingface.co/Qwen/Qwen3.8-27B - https://huggingface.co/incoai/Qwen3.8-27B-DFlash2 - add info Open weights apache-2.0 [View model](https://savrn.com/models/qwen3-8-27b-gguf-3) Model · Image and text to text ### [Huihui-Qwen3.8-27B-abliterated-GGUF](https://savrn.com/models/huihui-qwen3-8-27b-abliterated-gguf) [Huihui.ai](https://savrn.com/model-publishers/huihui-ai) This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added Huihui-Qwen3.8-27B-abliterated-Underdog-Saluki series come from ConwayResearch/Underdog-Saluki-27B-1.0 and ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF. Only layers 22 to 52 (0-based indexing) have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. Due to ConwayResearch/Underdog-Saluki-27B-1.0 not providing an imatrix file, we will attempt to perform ablation by mixing the GGUF… Open weights apache-2.0 transformers [View model](https://savrn.com/models/huihui-qwen3-8-27b-abliterated-gguf) Model · Image and text to text ### [Qwen3.8-27B-Uncensored-HauhauCS-Aggressive-MTP-GGUF](https://savrn.com/models/qwen3-8-27b-uncensored-hauhaucs-aggressive-mtp-gguf) [HauhauCS](https://savrn.com/model-publishers/hauhaucs) Qwen3.8-27B uncensored by HauhauCS 0/465 Refusals. This is the Aggressive variant: direct answers, no refusal behavior, and minimal preamble on hard prompts. Every text GGUF preserves Qwen3.8's native NextN head, and this release adds HauhauCS FastMTP: a specific acceleration sidecar qualified across the complete quant lineup at maximum native context. Vision is included through the separate BF16 projector. No changes to datasets or intended capabilities. This release preserves Qwen3.8-27B's text, reasoning, agentic, image, and video capabilities while applying the HauhauCS Aggressive uncensoring profile. Pick Aggressive when you specifically want the model to get to the answer without… Open weights apache-2.0 [View model](https://savrn.com/models/qwen3-8-27b-uncensored-hauhaucs-aggressive-mtp-gguf) Model · Image and text to text ### [Qwen3.5-9B-The-Defiant-Fable-Uncensored-Heretic-NEO-IMATRIX-MAX-MTP-GGUF](https://savrn.com/models/qwen3-5-9b-the-defiant-fable-uncensored-heretic-neo-imatrix-max-mtp-gguf) [David Belton](https://savrn.com/model-publishers/davidau) and it does so in 4bit and 8bit. Regular and MTP (fast) NEO IMATRIX GGUFs provided. (this model is part of the Qwen 3.6 27B Fable Fusion 711 pipelines: 2200+ likes, 3 million + downloads) instruct modes (2 new - Spoon / Einstein, all use ZERO REASONING TOKENS) all switchable on the fly via API, direct and "in chat" (yes - model ctrl at the chat/message level). Model name has "plusIQ" in the name. A 12+12 (12 reasoning and 12 instruct) model with interactive optimization/help system will be releasing shortly too. BF16/16-bit MTP GGUF also avail. (there is also a extra robust "tools" version too - Q6 and Q8.) Extreme intelligence in a small package. Jaw dropping performance. Superior… Open weights apache-2.0 [View model](https://savrn.com/models/qwen3-5-9b-the-defiant-fable-uncensored-heretic-neo-imatrix-max-mtp-gguf) ## HauhauCS [All models and datasets](https://savrn.com/model-publishers/hauhaucs) ## Versions - [ae8045ac2bd2](https://savrn.com/models/gemma4-12b-qat-uncensored-hauhaucs-balanced/versions/ae8045ac2bd2) · current 2026-10-10 ## Explore More - [All image and text to text models](https://savrn.com/models/tasks/image-and-text-to-text) - [All models under gemma](https://savrn.com/models/licenses/gemma) - [Model comparisons](https://savrn.com/models/comparisons) - [The model directory](https://savrn.com/models) - [Open model prices by host](https://savrn.com/ai-index/pricing/open-models) ## Source - Repository metadata, read 2026-10-10. - [Hugging Face record](https://huggingface.co/HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced) - [How the hub is built](https://savrn.com/model-hub/methodology)