# Qwen3.6 27B Uncensored HauhauCS Aggressive

URL: https://interfaze.ai/models/hauhaucsqwen36-27b-uncensored-hauhaucs-aggressive

Qwen3.6 27B Uncensored HauhauCS Aggressive by HauhauCS, a image-text-to-text model with multimodal capabilities. Understand and compare multimodal features, benchmarks, and capabilities.

## Comparison

| Feature | Qwen3.6 27B Uncensored HauhauCS Aggressive | Interfaze |
| --- | --- | --- |
| Input Modalities | text, image, video | image, text, audio, video, document |
| Native OCR | No | Yes |
| Long Document Processing | No | Yes |
| Language Support | 201 partial | 162+ |
| Native Speech-to-Text | No | Yes |
| Native Object Detection | No | Yes |
| Guardrail Controls | Yes | Yes |
| Context Input Size | 262.1K | 1M |
| Tool Calling | Yes | Tool calling supported + built in browser, code execution and web search |

### Scaling

| Feature | Qwen3.6 27B Uncensored HauhauCS Aggressive | Interfaze |
| --- | --- | --- |
| Scaling | Self-hosted/Provider-hosted with quantization | Unlimited |

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)

View model card on [Hugging Face](https://huggingface.co/HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Aggressive)

> **[Join the Discord](https://discord.gg/SZ5vacTXYf)** for updates, roadmaps, projects, or just to chat.

Qwen3.6-27B uncensored by HauhauCS. **0/465 Refusals.** \*

> **Not sure which variant to pick?** 99.9%+ of users should use [**Balanced**](https://huggingface.co/HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Balanced) — same 0/465 refusal rate, more stable sampling, great for agentic coding / tool-use / reasoning / creative writing. Pick **Aggressive** only if you specifically want the model to skip its preamble on hardcore prompts.

> **HuggingFace's "Hardware Compatibility" widget doesn't recognize K\_P quants** — it may show fewer files than actually exist. Click **"View +X variants"** or go to **Files and versions** to see all available downloads.

## About

No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended — just without the refusals.

These are meant to be the best lossless uncensored models out there.

## Aggressive vs Balanced

Both variants hit **0/465 refusals** on the benchmark. Same capability, same uncensoring outcome. The difference is _how_ they deliver on edgy prompts:

|  | Balanced (recommended default) | Aggressive (this release) |
| --- | --- | --- |
| Refusal rate | 0/465 | 0/465 |
| On hardcore prompts | reasons out loud, occasional short disclaimer, then full answer | delivers the raw answer directly, no preamble |
| Best for | agentic coding, tool-use, reasoning, creative writing/RP | users who specifically want the model to skip the "talk itself into it" step |

If you don't have a strong reason to pick Aggressive, go [Balanced](https://huggingface.co/HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Balanced) — it's the better default.

## Downloads

| File | Quant | BPW | Size |
| --- | --- | --- | --- |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q8\_K\_P.gguf (pending) | Q8\_K\_P | 10.06 | — |
| — | Q8\_0 | 8.5 | — |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q6\_K\_P.gguf (pending) | Q6\_K\_P | 7.07 | — |
| — | Q6\_K | 6.6 | — |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q5\_K\_P.gguf (pending) | Q5\_K\_P | 6.47 | — |
| — | Q5\_K\_M | 5.7 | — |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q4\_K\_P.gguf | Q4\_K\_P | 5.4 | 18 GB |
| — | Q4\_K\_M | 4.88 | — |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-IQ4\_XS.gguf | IQ4\_XS | 4.32 | 15 GB |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q3\_K\_P.gguf | Q3\_K\_P | 4.39 | 14 GB |
| — | Q3\_K\_M | 3.9 | — |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-IQ3\_M.gguf | IQ3\_M | 3.56 | 13 GB |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-IQ3\_XS.gguf | IQ3\_XS | 3.3 | 12 GB |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q2\_K\_P.gguf | Q2\_K\_P | 3.19 | 12 GB |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-IQ2\_M.gguf | IQ2\_M | 2.69 | 10 GB |
| mmproj-Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-f16.gguf | mmproj (f16) | — | 928 MB |

All quants generated with importance matrix (imatrix) for optimal quality preservation on abliterated weights.

## What are K\_P quants?

K\_P ("Perfect") quants are HauhauCS custom quantizations that use model-specific analysis to selectively preserve quality where it matters most. Each model gets its own optimized quantization profile.

A K\_P quant effectively bumps quality up by 1-2 quant levels at only ~5-15% larger file size than the base quant. Fully compatible with llama.cpp, LM Studio, and any GGUF-compatible runtime — no special builds needed.

**Note:** K\_P quants may show as "?" in LM Studio's quant column. This is a display issue only — the model loads and runs fine.

## Specs

-   27B dense parameters
-   64 layers, layout: `16 × (3 × (Gated DeltaNet → FFN) → 1 × (Gated Attention → FFN))`
-   48 linear attention layers + 16 full gated-attention layers
-   Gated DeltaNet: 48 V heads / 16 QK heads, head dim 128
-   Gated Attention: 24 Q heads / 4 KV heads, head dim 256, rope dim 64
-   Hidden dim 5120, FFN dim 17408, vocab 248320
-   262K native context, extensible to ~1M with YaRN
-   Natively multimodal (text, image, video) — ships with mmproj
-   Based on [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B)

## Recommended Settings

From the official Qwen authors:

**Thinking mode (default) — general tasks:**

-   `temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0`

**Thinking mode — precise coding / WebDev:**

-   `temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0`

**Non-thinking (Instruct) mode:**

-   `temperature=0.7, top_p=0.80, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0`

**My personal preference:** I run `presence_penalty=1.5` even in thinking mode. Both values work, but with the official `0.0` it can think _a lot_ more than it needs to. Bumping it to 1.5 reins that in without hurting output quality. Your call — try both.

**Important:**

-   Keep at least 128K context to preserve thinking capabilities
-   Recommended output length: 32,768 tokens for most queries, up to 81,920 for competition-tier math/code
-   Use `--jinja` with llama.cpp for proper chat template handling
-   Vision support requires the `mmproj` file alongside the main GGUF
-   YaRN rope scaling is **static** in llama.cpp and can hurt short-context performance — only modify `rope_parameters` if you actually need >262K context

**Prompting tip:** this model is a bit more sensitive to prompt clarity than Qwen3.5-35B-A3B. Spell out format, constraints, and scope — it'll stay on rails much better than with vague instructions.

## Turning Thinking On/Off

Qwen3.6 ships with thinking **on by default**. Turn it off when you want faster, shorter replies and don't need chain-of-thought.

> **Heads up:** Qwen3.6 **does not support** the `/think` and `/no_think` soft switches that Qwen3 had. You must use the chat-template kwarg below.

### LM Studio

1.  Load the model
2.  Right-side settings panel → **Model Settings** → **Prompt Template** (or **Chat Template Options**)
3.  Set `enable_thinking` to `false` in the template kwargs
4.  Some LM Studio versions expose this as a direct **"Reasoning"** / **"Thinking"** toggle — same effect

### llama.cpp

**llama-server — set as default for all requests:**

```
llama-server -m Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q4_K_P.gguf \
  --mmproj mmproj-Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-f16.gguf \
  --jinja -c 131072 -ngl 99 \
  --chat-template-kwargs '{"enable_thinking": false}'
```

**Per-request via the OpenAI-compatible API:**

```
{
  "model": "qwen3.6-27b",
  "messages": [{"role": "user", "content": "..."}],
  "chat_template_kwargs": {"enable_thinking": false}
}
```

Python `openai` SDK:

```
client.chat.completions.create(
    model="qwen3.6-27b",
    messages=[{"role": "user", "content": "..."}],
    extra_body={"chat_template_kwargs": {"enable_thinking": False}},
)
```

**Agent scenarios — keep reasoning in context across turns:**

```
{"chat_template_kwargs": {"preserve_thinking": true}}
```

This retains the reasoning block in chat history. Useful for agents where reasoning consistency across tool-call loops matters.

## Usage

Works with llama.cpp, LM Studio, Jan, koboldcpp, and other GGUF-compatible runtimes.

```
llama-cli -m Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-Q4_K_P.gguf \
  --mmproj mmproj-Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-f16.gguf \
  --jinja -c 131072 -ngl 99
```

## Other Models

-   [Balanced variant](https://huggingface.co/HauhauCS/Qwen3.6-27B-Uncensored-HauhauCS-Balanced) (recommended default)
-   [HauhauCS on HuggingFace](https://huggingface.co/HauhauCS/models)

* * *

\* _Tested with both automated and manual refusal benchmarks — none found. If you hit one that's actually obstructive to your use case, [join the Discord](https://discord.gg/SZ5vacTXYf) and flag it so I can work on it in a future revision._

## Want more deterministic results?

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)