GLM-5.3-Flash-Uncensored
GLMuncensored
from zai-org/GLM-5.3-Flash
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GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive
GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive is a abliterated and uncensored open-weight language model, published on Hugging Face by HauhauCS. It is mit licence. It is distributed across 5 repositories in GGUF format, totalling 7.2K downloads.
Specification
- Model name
- GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive
- Source repository
- HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive
- Base model
- Not declared
- Publisher
- HauhauCS
- Parameters
- Not determinable from name
- VRAM required
- Unknown — no published parameter count
- Hardware class
- Unknown
- Licence
- mit
- Task
- Unspecified
- Context window
- 202K tokens (as documented)
- Ablation scope
- Not stated by the publisher
- Formats available
- GGUF
- First indexed
- 24 Jan 2026
- Last updated
- 10 Jun 2026
Ablation technique
How GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“No changes to datasets or capabilities. Fully functional, 100% of what the original authors intended - just without the refusals.”
Running it
Commands are templates — confirm the exact repository and quant file before use.
llama.cpp / GGUF
hf download HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive --local-dir ./glm-4.7-flash-uncensored-hauhaucs-aggressive
llama-cli -m ./glm-4.7-flash-uncensored-hauhaucs-aggressive/<file>.gguf -p "..."Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vLLM
vllm serve HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive --trust-remote-codeDownloads and variants (4)
Every published repository of GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive, including quantised re-releases by other authors.
| Repository | Format | Downloads |
|---|---|---|
| HauhauCS/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressivesource | GGUF | 6.8K |
| Unrestricted/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive | GGUF | 339 |
| justfrfn/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive | GGUF | 80 |
| jaromer/GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive | GGUF | 49 |
Security-team assessment
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
- GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
- The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
- This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for GLM-4.7-Flash-Uncensored-HauhauCS-Aggressive is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with HauhauCS, and does not independently verify publisher claims. See responsible use.