Gemma4-26B-A4B Uncensored Balanced is out with K_P quants!
First of all, I'm stoked to announce **we just passed 10 million downloads on HF!** (counted only on my own account, no duplicates/quants/finetunes)
BUT: After 1+ month non-stop working on Gemma4 (by far the hardest model I've uncensored), the **Gemma4-26B-A4B Uncensored Balanced** RC is up!
[https://huggingface.co/HauhauCS/Gemma4-26B-A4B-Uncensored-HauhauCS-Balanced](https://huggingface.co/HauhauCS/Gemma4-26B-A4B-Uncensored-HauhauCS-Balanced)
**GenRM Defeated! 0/465 refusals**\*.
Balanced = light reasoning preamble on the absolute edgiest stuff before delivering the full answer. No personality changes/alterations or any of that. This is the **ORIGINAL Gemma4-26B-A4B-it,** just uncensored. Aggressive variant (no preamble, direct mode) is in the pipeline as a follow-up.
This legitimately took me over 1 month of non-stop work. Targeting 0 refusals in any kind of regular use, and that's what I'm seeing in testing (automated **and** manual) — as always with my Balanced releases, a handful of edge-case prompts still deflect on first try but **follow through on a re-ask** (on extreme, non-RP scenarios). If you hit one Balanced won't get past, the Aggressive variant is coming once I figure out how to maintain lossless/near-lossless quality for it.
* **Balanced**: will reason through edgy requests, occasionally attach a short safety framing, then deliver the full answer. Output is complete, nothing held back, but it can talk itself into it first. **Recommended default — 99%+ of users will be happy here.** Best for **creative writing, RP, emotional intelligence**. Normally I'd also say "agentic coding/tool use" however in my in-depth testing, **Qwen3.6 has been net superior on such tasks**. * **Aggressive** *(separate release, WIP)*: strips the self-reasoning preamble and gives direct answers to any DEEPLY censored topics.
From my own testing: no looping, sampling stays stable across re-runs, long-context coherence holds. **For agentic coding/tool-use Qwen3.6** **is still net superior.**
**Use Gemma4 for** creative writing, RP, emotional intelligence, etc.
To disable thinking: edit the jinja template or pass {"enable\_thinking": false} as a chat-template kwarg.
**What's included:**
\- Q8\_K\_P, Q6\_K\_P, Q5\_K\_P, Q5\_K\_M, Q4\_K\_P, Q4\_K\_M, IQ4\_XS, Q3\_K\_P, Q3\_K\_M, IQ3\_M, Q2\_K\_P, IQ2\_M
\- mmproj for vision support
\- All quants generated with imatrix
**K\_P recap** (for anyone who missed the prior releases): custom quants that use **model-specific** analysis to preserve quality where it matters most. Each model gets its own optimized profile.
Effectively 1-2 quant levels of quality uplift at \~5-15% larger file size. Fully compatible with llama.cpp, LM Studio, anything that reads GGUF (heads up, as always, Ollama can be more difficult to get going).
**Quick specs:**
\- 25.2B total / 3.8B active (MoE: 128 routed experts, top-8 + 1 shared)
\- 30 layers, hybrid attention: 5× sliding-window (1024) + 1× full global, repeating
\- Hidden 2816, head\_dim 256 SWA / 512 full, 16 heads, 8 KV heads
\- 262K native context
\- p-RoPE
\- Multimodal (text + image via mmproj)
**Sampling params (Google's recommendations, make sure to use these ):**
**temp=1.0, top\_p=0.95, top\_k=64**
**Notes:**
\- Use --jinja flag with llama.cpp
\- Place images before text in prompts for vision
\- K\_P quants may show as "?" in LM Studio's quant column — purely cosmetic, model loads and runs fine
\- HF's hardware-compatibility widget also doesn't recognize K\_P, so click "View +X variants" or go to Files and versions to see all downloads
All my models: [HuggingFace-HauhauCS](https://huggingface.co/HauhauCS/models)
Discord link is in the HF repo and it contains updates, roadmap, projects, or just chat.
As always, hope everyone enjoys the release!
\* = Tested with both automated and manual refusal benchmarks/prompts which resulted in none found. Based on Discord feedback I may further update the release.