Model overview
> **Qwen3.8-27B-abliterated-GGUF** is a GGUF-quantized conversion of huihui-ai/Huihui-Qwen3.8-27B-abliterated, an uncensored variant of Qwen/Qwen3.8-27B produced through abliteration — a crude, proof-of-concept activation-editing technique that removes refusal behavior directly from model weights without relying on TransformerLens. The underlying Qwen3.8-27B is a 27-billion-parameter dense causal language model with a native vision encoder, built on the Qwen3.5 architectural foundation, featuring a 64-layer hybrid design interleaving Gated DeltaNet linear-attention blocks with periodic Gated Attention layers, Multi-Token Prediction (MTP) training, a native 262,144-token context window extensible to 1M via YaRN, native image/video understanding, and flexible thinking control through a `reasoning_effort` parameter, delivering strong results on benchmarks like SWE-bench Pro (61.7), OSWorld-Verified (84.3), and GPQA Diamond (89.2). This GGUF release packages the abliterated weights across the standard quantization sweep for efficient local deployment via llama.cpp and compatible runtimes; note that, as with GGUF conversions generally, **the Multi-Token Prediction (MTP) heads are not preserved** in this format — the model runs as a standard single-token-per-step autoregressive decoder, so any latency or quality benefits tied to MTP-based speculative decoding in the original checkpoint do not carry over to these quantized builds. File Name | Quant Type | File Size | File Link | |-----------|------------|-----------|-----------| | Qwen3.8-27B-abliterated.BF16.gguf | BF16 | 53.8 GB | Download | | Qwen3.8-27B-abliterated.F16.gguf | F16 | 53.8 GB | Download | | Qwen3.8-27B-abliterated.Q2_K.gguf | Q2_K | 10.7 GB | Download | | Qwen3.8-27B-abliterated.Q3_K_L.gguf | Q3_K_L | 14.3 GB | Download | | Qwen3.8-27B-abliterated.Q3_K_M.gguf | Q3_K_M | 13.3 GB | Download | | Qwen3.8-27B-abliterated.Q3_K_S.gguf | Q3_K_S | 12.1 GB | Download | | Qwen3.8-27B-abliterated.Q4_0.gguf | Q4_0 | 15.5 GB | Download | | Qwen3.8-27B-abliterated.Q4_K_M.gguf | Q4_K_M | 16.5 GB | Download | | Qwen3.8-27B-abliterated.Q4_K_S.gguf | Q4_K_S | 15.6 GB | Download | | Qwen3.8-27B-abliterated.Q5_0.gguf | Q5
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。