Qwen3-VL-8B-Thinking-abliterated-v1-GGUF
The Qwen3-VL-8B-Thinking-abliterated-v1 from prithivMLmods is an 8B-parameter vision-language model, an abliterated (v1.0) variant of Alibaba's Qwen3-VL-8B-Thinking optimized for uncensored reasoning and captioning across complex, sensitive, nuanced, artistic, technical, or abstract visual/multimodal content while supporting diverse aspect ratios, resolutions, videos, and layouts with Interleaved-MRoPE, 32-language OCR, and 256K+ context length. It bypasses standard content filters to generate factual, descriptive, reasoning-rich outputs with variational detail control—from high-level summaries to intricate chain-of-thought analyses—leveraging the base model's superior visual agent capabilities, spatial perception, long-context video understanding, and STEM reasoning, primarily in English with multilingual prompt adaptability.[attached_file:1 equivalent] Ideal for research in content moderation/red-teaming, creative storytelling, and visual datasets excluded from mainstream models, it uses Transformers/Qwen3VLForConditionalGeneration for GPU inference (16-24GB VRAM) but may produce explicit content unsuitable for moderated production.
Qwen3-VL-8B-Thinking-abliterated-v1
| File Name | Quant Type | File Size | File Link |
|---|---|---|---|
| Qwen3-VL-8B-Thinking-abliterated-v1.IQ4_XS.gguf | IQ4_XS | 4.59 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q2_K.gguf | Q2_K | 3.28 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q3_K_L.gguf | Q3_K_L | 4.43 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q3_K_M.gguf | Q3_K_M | 4.12 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q3_K_S.gguf | Q3_K_S | 3.77 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q4_K_M.gguf | Q4_K_M | 5.03 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q4_K_S.gguf | Q4_K_S | 4.8 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q5_K_M.gguf | Q5_K_M | 5.85 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q5_K_S.gguf | Q5_K_S | 5.72 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q6_K.gguf | Q6_K | 6.73 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.Q8_0.gguf | Q8_0 | 8.71 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.f16.gguf | F16 | 16.4 GB | Download |
| Qwen3-VL-8B-Thinking-abliterated-v1.mmproj-Q8_0.gguf | mmproj-Q8_0 | 752 MB | Download |
| Qwen3-VL-8B-Thinking-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-Thinking-abliterated-v1-GGUF
Base model
Qwen/Qwen3-VL-8B-Thinking