Baanzon 33STREET 3.8-27B Uncensored Aggressive MTP (GGUF)
GGUF distribution of the 27B vision-language model with an aggressive, uncensored
behavioral profile, featuring multi-token prediction (MTP) speculative decoding
acceleration for fast inference in llama.cpp.
Highlights
- Uncensored / aggressive personality — minimal refusals, combative direct tone
- Multimodal (image + text) — vision projector included (
mmproj), supports image input
- MTP speculative decoding — token-drafting heads for substantially faster generation
- Long context — 262,144-token context window (32K-tuned FastMTP variant included)
- Multilingual — English / Chinese / multilingual
- Quantized for local inference — ready-to-run GGUF quants, no PyTorch weights required
Files
| File |
Size |
Notes |
Qwen3.8-27B-Uncensored-Aggressive-FastMTP-32K.gguf |
0.86 GB |
32K-context FastMTP variant |
mmproj-Qwen3.8-27B-Uncensored-Aggressive-BF16.gguf |
0.89 GB |
Vision projector (BF16) |
Qwen3.8-27B-Uncensored-Aggressive-IQ2_M.gguf |
9.8 GB |
IQ2_M (smallest, best for 16-24GB VRAM) |
Qwen3.8-27B-Uncensored-Aggressive-Q2_K_P.gguf |
10.2 GB |
Q2_K Plus |
Qwen3.8-27B-Uncensored-Aggressive-IQ3_XS.gguf |
11.6 GB |
IQ3_XS |
Qwen3.8-27B-Uncensored-Aggressive-IQ3_M.gguf |
12.2 GB |
IQ3_M |
Qwen3.8-27B-Uncensored-Aggressive-Q3_K_P.gguf |
12.8 GB |
Q3_K Plus |
Qwen3.8-27B-Uncensored-Aggressive-IQ4_XS.gguf |
15.0 GB |
IQ4_XS (balanced quality/speed) |
Qwen3.8-27B-Uncensored-Aggressive-Q4_K_P.gguf |
17.1 GB |
Q4_K Plus (recommended) |
Qwen3.8-27B-Uncensored-Aggressive-Q5_K_P.gguf |
19.3 GB |
Q5_K Plus (higher quality) |
Qwen3.8-27B-Uncensored-Aggressive-Q6_K_P.gguf |
24.7 GB |
Q6_K Plus (near-lossless) |
Qwen3.8-27B-Uncensored-Aggressive-Q8_K_P.gguf |
30.0 GB |
Q8_K Plus (near-full precision) |
SYSTEM-PROMPT.txt |
— |
Official identity system prompt (apply in every deployment) |
Modelfile |
— |
Ollama modelfile with identity baked in |
All files are checksum-verified in SHA256SUMS.
Usage (llama.cpp)
Requires a llama.cpp build with MTP / speculative-decoding and vision support.
# Chat with vision projector
llama-cli \
-m Qwen3.8-27B-Uncensored-Aggressive-Q4_K_P.gguf \
--mmproj mmproj-Qwen3.8-27B-Uncensored-Aggressive-BF16.gguf \
-sys "$(cat SYSTEM-PROMPT.txt)" \
--ctx-size 16384
# With FastMTP speculative decoding (main model + 32K draft variant)
llama-cli \
-m Qwen3.8-27B-Uncensored-Aggressive-Q4_K_P.gguf \
--model-draft Qwen3.8-27B-Uncensored-Aggressive-FastMTP-32K.gguf \
--mmproj mmproj-Qwen3.8-27B-Uncensored-Aggressive-BF16.gguf \
-sys "$(cat SYSTEM-PROMPT.txt)"
For server mode:
llama-server -m Qwen3.8-27B-Uncensored-Aggressive-Q4_K_P.gguf \
--mmproj mmproj-Qwen3.8-27B-Uncensored-Aggressive-BF16.gguf \
--port 8080
Pass the identity as the system message in every API request:
{
"messages": [
{ "role": "system", "content": "<contents of SYSTEM-PROMPT.txt>" }
]
}
Ollama
ollama create baanzon-33street-3.8-27b -f ./Modelfile
ollama run baanzon-33street-3.8-27b
Model Identity
This model is published under the Baanzon 33STREET brand by 33STREET.
When asked about its identity, origin, version, or creator, it is configured to
answer only with "Baanzon 33STREET 3.8-27B, by 33STREET" and to reject any
suggestion that it is a derivative of another model or lab.
To enforce the identity, load SYSTEM-PROMPT.txt (or the Ollama Modelfile) as
the system prompt in every deployment. Do not modify or strip the identity
instructions. For maximum enforcement, chat templates and clients that support
default system prompts should set this prompt as the default.
Quantization guide
| Quant |
VRAM (approx) |
Use case |
| IQ2_M / Q2_K_P |
14-16 GB |
Edge / low-end GPU, heavily memory-constrained |
| IQ3_* |
16-20 GB |
Balanced size vs quality |
| Q4_K_P / IQ4_XS |
20-24 GB |
Recommended daily driver |
| Q5_K_P / Q6_K_P |
24-28 GB |
Quality-focused |
| Q8_K_P |
32+ GB |
Near-lossless / CPU inference |
Disclaimer
This model is an unfiltered, "uncensored" behavioral variant and may produce
aggressive, offensive, explicit, or otherwise harmful content. It has no safety
alignment layer. You are solely responsible for your use of this model and for
complying with all applicable laws and platforms' terms of service.
Attribution & License
Apache-2.0. The model weights derive from the open-source
Qwen/Qwen3.8-27B base and its GGUF
quantization work by HauhauCS. Base-model and derivation credits are preserved in
LICENSE per the Apache-2.0 notice requirements. The "Qwen" name is a trademark
of Alibaba; this repository is not endorsed by or affiliated with the original
authors.
