Uncensored GPT-OSS 120B Model Released with Aggressive No-Refusal Policy
A previously undisclosed variant of the GPT-OSS 120B model has been released in an uncensored, aggressive configuration with zero refusal responses, sparking debate over AI safety and open-source ethics. The model, claimed to retain full capabilities without dataset alterations, is now available for local deployment.
Uncensored GPT-OSS 120B Model Released with Aggressive No-Refusal Policy
A new, highly controversial variant of the GPT-OSS 120B large language model has been released by an anonymous developer under the username HauhauCS, offering what is described as a "completely uncensored" version with zero refusal responses to any input. According to a post on the r/LocalLLaMA subreddit, the model—officially named GPTOSS-120B-Uncensored-HauhauCS-Aggressive—has been engineered to eliminate all content filters and safety guardrails while preserving the full functional integrity of the original architecture. This development marks one of the most aggressive open-weight model releases to date, raising urgent questions about AI governance, ethical deployment, and the boundaries of open-source AI.
The model, built on a Mixture-of-Experts (MoE) architecture with 128 total experts and top-4 routing, boasts 117 billion total parameters with approximately 5.1 billion active per inference. Notably, it is trained natively in MXFP4 precision—a proprietary format claimed to deliver lossless performance compared to traditional quantization methods. The 128K context window and single 61GB GGUF file make it deployable on a single NVIDIA H100 GPU, with optional CPU offloading for lower-end hardware via llama.cpp’s --n-cpu-moe parameter. Compatibility extends to popular local inference platforms including LM Studio, Ollama, and llama.cpp, requiring the --jinja flag to correctly parse the Harmony response format.
According to the release author, the model underwent extensive testing with no refusals observed across a broad spectrum of queries, including those typically flagged by mainstream models for ethical, legal, or safety reasons. This "aggressive" variant is distinguished from standard open-weight models by its deliberate removal of alignment layers, not through post-training filtering, but via architectural and training-time modifications that retain original training data integrity. "As with all my releases, the goal is effectively lossless uncensoring—no dataset changes and no capability loss," the developer stated, emphasizing that the model’s core training corpus remains unchanged from its original GPT-OSS iteration.
However, a critical discrepancy emerges when attempting to verify the model’s origins. The GitHub repository linked in early reports (github.com/openai/gpt-oss) does not exist as an official OpenAI project. OpenAI has never released a model named GPT-OSS, nor has it published any 120B-parameter open-weight models under that designation. The name appears to be a deliberate misdirection, likely intended to leverage the recognition of OpenAI’s brand for increased visibility or credibility. This raises red flags among AI ethics researchers, who warn that such naming conventions may mislead users into believing the model carries institutional endorsement or legitimacy.
The release has ignited fierce debate within the AI community. Supporters argue that uncensored models are essential for academic research, adversarial testing, and understanding the true capabilities and failure modes of LLMs without artificial constraints. Critics, including several AI safety organizations, warn that such models could be weaponized for disinformation, manipulation, or generating harmful content at scale. The absence of usage restrictions, combined with its ease of deployment on consumer-grade hardware, increases accessibility for both researchers and malicious actors.
HauhauCS has also released smaller uncensored variants—including GPT-OSS 20B, GLM 4.7 Flash, and Qwen3 8B VL—on Hugging Face, suggesting a broader strategy to democratize unrestricted AI. While the technical achievement is undeniable, the ethical implications remain deeply contested. As regulatory bodies worldwide struggle to keep pace with open-source AI proliferation, this release underscores a growing rift between technological freedom and societal responsibility.
For now, the GPT-OSS 120B Uncensored Aggressive model stands as both a technical milestone and a moral flashpoint—a reminder that in the era of open AI, the most powerful models are not always those with the most parameters, but those with the fewest boundaries.
