Felldude releases uncensored Ministral3 3B as GGUF for CPU inference
A new GGUF quantization of Felldude's uncensored Ministral3 3B model is now available on HuggingFace, optimized for local inference on consumer hardware without a dedicated GPU.
Felldude-Uncensored-Ministral3-3B-GGUF, a quantized version of Felldude's uncensored Ministral3 3B model, is now available on HuggingFace. The GGUF format makes the 3-billion-parameter conversational model runnable on consumer hardware without a dedicated GPU, enabling inference on laptops and older desktops.
GGUF quantization typically cuts memory footprint by 50–75 percent compared to full-precision weights. The "uncensored" label indicates the model lacks the safety filters common in commercial LLMs, making it suitable for practitioners who need unrestricted text generation without content moderation.
What stands out:
- 01GGUF format for CPU inference — Quantized weights let users run the 3B model on machines without high-end GPUs, a key advantage for local deployment.
- 02Uncensored baseline — The model is explicitly unfiltered, enabling unrestricted text generation without content moderation.
- 033B parameter size — At three billion parameters, the model sits in the sweet spot for fast inference on consumer hardware while retaining conversational coherence.
- 04US region hosting — The weights are hosted in HuggingFace's US region, relevant for latency-sensitive deployments.