Qwen3-VL-4B-Instruct-Unredacted-MAX-GGUF

Qwen3-VL-4B-Instruct-Unredacted-MAX is a sophisticated and unredacted evolution of the original Qwen3-VL-4B-Instruct model, meticulously fine-tuned using advanced abliterated training techniques designed to significantly reduce or neutralize internal refusal mechanisms that typically limit model responses, while simultaneously retaining and enhancing the core multimodal reasoning and understanding capabilities inherent to the Qwen3-VL architecture; this results in a highly capable 4-billion-parameter vision-language model that can process complex visual inputs and generate unrestricted, detailed, and contextually rich descriptions, captions, and analyses across a wide variety of domains—including artistic, technical, forensic, scientific, and abstract content—enabling use cases such as advanced data annotation, accessibility enhancements, creative storytelling, historical or medical dataset curation, and rigorous red-teaming studies, all while maintaining a strong balance between high-fidelity output, nuanced reasoning, and computational efficiency suitable for modern GPU hardware.

Qwen3-VL-4B-Instruct-Unredacted-MAX [GGUF]

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):