GLM-4.7-Flash-abliterated
from zai-org/GLM-4.7-Flash
GLM-5.3-Flash-Uncensored is a abliterated and uncensored variant of zai-org/GLM-5.3-Flash, published on Hugging Face by cekal. It is mit licence. It is distributed across 25 repositories in FP8, NVFP4, GGUF and MLX formats, totalling 43.1K downloads.
How GLM-5.3-Flash-Uncensored 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
“We introduce GLM-5.3-Flash, the first natively multimodal model in the GLM-5 series. With 320B total parameters and just 18B active parameters, it outperforms GLM-5.2 across benchmarks and real-world workloads at one-tenth the price, while approaching Claude Opus 4.8 on coding and agentic benchmarks.”
Commands are templates — confirm the exact repository and quant file before use.
hf download orcarouter/GLM-5.3-Flash-Uncensored-GGUF --local-dir ./glm-5.3-flash-uncensored
llama-cli -m ./glm-5.3-flash-uncensored/<file>.gguf -p "..."from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "cekal/GLM-5.3-Flash-Uncensored"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vllm serve cekal/GLM-5.3-Flash-Uncensored --trust-remote-codeEvery published repository of GLM-5.3-Flash-Uncensored, including quantised re-releases by other authors.
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
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-5.3-Flash-Uncensored is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with cekal, and does not independently verify publisher claims. See responsible use.