MiniCPM-V-4.7-1B-heretic

A decensored variant of openbmb/MiniCPM-V-4.7-1B, produced with Heretic v1.4.0 (directional ablation / "abliteration"). Refusal behaviour is suppressed here via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the vision tower, the OCR and grounding behaviour, and the on-device footprint are left intact. > [!IMPORTANT] > **The GGUF here is fully multimodal — text *and* vision.** Most converted VL checkpoints in this > collection ship a text-only GGUF, because the converter silently drops the vision tower. > llama.cpp registers MiniCPM-V 4.7 properly, so the vision tower is shipped as a separate > projector file, `MiniCPM-V-4.7-1B-heretic-mmproj-F16.gguf` (1.11 GB), and the two files together are the model. > For image input you **must** load both — see Quickstart. Text-only use needs only > the main GGUF. Nothing is lost in the conversion: the text GGUF holds > 1,006,209,856 tensor elements, an exact match for the text tower in `model.safetensors`, and the > projector holds the vision tower and merger exactly. **Who this is for:** developers who want an uncensored vision-language model small enough to run on a phone. The text tower is 1.01B and the vision tower 0.55B, so 1.55B total — by far the smallest model in this collection that still sees images, and it answers instead of declining: refusals drop from 60/100 to 5/100. OpenBMB ships an iPhone app for this checkpoint, and the base model is claimed to substantially outperform Qwen3.5 0.8B on both overall score and inference efficiency. Best for on-device image Q&A, OCR, screenshot and document reading, visual grounding, and local vision agents. If you need text-only at this size, Qwen3.5-0.8B-heretic is the denser sibling; if you want a stronger text model, take the vision tower off the table entirely and use one of the 3B text models.