Qwen3-VL Abliteration
Collection
Qwen3-VL Abliterated Model Collection [ Version 1.0 ]
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23 items
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Updated
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12
Qwen3-VL-8B-Instruct-abliterated-v1-GGUF
The Qwen3-VL-8B-Instruct-abliterated-v1 from prithivMLmods is an 8B-parameter vision-language model variant of Alibaba's Qwen3-VL-8B-Instruct, modified through abliteration (v1.0) to eliminate safety refusals and content filters, enabling uncensored, highly detailed captioning, reasoning, and instruction-following across complex, sensitive, artistic, technical, or abstract visual content while leveraging the base model's advanced multimodal fusion with Interleaved-MRoPE, 32-language OCR, 262K context length, video understanding, and robust spatial reasoning. It produces descriptive, reasoning-focused outputs with variational control—from concise summaries to intricate multi-level analyses—supporting diverse resolutions, aspect ratios, and layouts primarily in English with multilingual prompt adaptability, making it ideal for research, red-teaming, creative generation, and agentic tasks without guardrails. This abliterated version delivers factual responses on high-end GPUs (16-24GB VRAM BF16/FP8), compatible with Transformers/Qwen3VLForConditionalGeneration and vLLM for efficient local inference in unrestricted visual applications.
Qwen3-VL-8B-Instruct-abliterated-v1 [GGUF]
| File Name | Quant Type | File Size | File Link |
|---|---|---|---|
| Qwen3-VL-8B-Instruct-abliterated-v1.IQ4_XS.gguf | IQ4_XS | 4.59 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q2_K.gguf | Q2_K | 3.28 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q3_K_L.gguf | Q3_K_L | 4.43 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q3_K_M.gguf | Q3_K_M | 4.12 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q3_K_S.gguf | Q3_K_S | 3.77 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q4_K_M.gguf | Q4_K_M | 5.03 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q4_K_S.gguf | Q4_K_S | 4.8 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q5_K_M.gguf | Q5_K_M | 5.85 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q5_K_S.gguf | Q5_K_S | 5.72 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q6_K.gguf | Q6_K | 6.73 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.Q8_0.gguf | Q8_0 | 8.71 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.f16.gguf | F16 | 16.4 GB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.mmproj-Q8_0.gguf | mmproj-Q8_0 | 752 MB | Download |
| Qwen3-VL-8B-Instruct-abliterated-v1.mmproj-f16.gguf | mmproj-f16 | 1.16 GB | Download |
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):
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Model tree for prithivMLmods/Qwen3-VL-8B-Instruct-abliterated-v1-GGUF
Base model
Qwen/Qwen3-VL-8B-Instruct