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qwen3.8-27b-defiance-iq4
Defiance combines HauhauCS's uncensored Qwen3.8-27B weights with a
customized Turbo Brilliance chat template for reasoning and roleplay.
This IQ4_XS GGUF build uses llama.cpp and the embedded template,
with a 32,768-token context. Text input only; MTP is not enabled.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-defiance-q6
Defiance combines HauhauCS's uncensored Qwen3.8-27B weights with a
customized Turbo Brilliance chat template for reasoning and roleplay.
This Q6_K_P GGUF build uses llama.cpp and the embedded template,
with a 32,768-token context. Text input only; MTP is not enabled.
Repository: localaiLicense: apache-2.0
atomic-lfm2.5-24b-a2b-uncensored
AtomicChat's LFM2.5-24B-A2B derivative reduces refusal behavior in the
original weights. This text-only mixture-of-experts model has 24B total
parameters and supports multilingual reasoning and tool use.
This entry uses the AD-Q4_K_M GGUF build with the edits baked in.
Repository: localaiLicense: other
atomic-lfm2.5-24b-a2b-uncensored-q6
AtomicChat's LFM2.5-24B-A2B derivative reduces refusal behavior in the
original weights. This text-only mixture-of-experts model has 24B total
parameters and supports multilingual reasoning and tool use.
This entry uses the AD-Q6_K GGUF build with the edits baked in.
Repository: localaiLicense: other
atomic-lfm2.5-24b-a2b-uncensored-q8
AtomicChat's LFM2.5-24B-A2B derivative reduces refusal behavior in the
original weights. This text-only mixture-of-experts model has 24B total
parameters and supports multilingual reasoning and tool use.
This entry uses the AD-Q8_0 GGUF build with the edits baked in.
Repository: localaiLicense: other
atomic-minicpm-v-4.7-35b-a3b-uncensored-q4
AtomicChat's abliterated MiniCPM-V 4.7 is a 35B mixture-of-experts model
with 3B active parameters for chat and image understanding. This
AD-Q4_K-IQ4_XS build includes all 11 weight shards and the F16 vision
projector, with the embedded chat template and a 32K-token default context.
Repository: localaiLicense: apache-2.0
atomic-minicpm-v-4.7-35b-a3b-uncensored-q6
AtomicChat's abliterated MiniCPM-V 4.7 is a 35B mixture-of-experts model
with 3B active parameters for chat and image understanding. This
AD-Q6_K build includes all 16 weight shards and the F16 vision
projector, with the embedded chat template and a 32K-token default context.
Repository: localaiLicense: apache-2.0
underdog-saluki-27b-1.0-abliterated
Kujira's abliterated adaptation of Underdog Saluki 27B 1.0 uses mixed
IQ2 weights with an embedded MTP head. This text-only llama.cpp build
uses ordinary decoding; the MTP variant enables speculative decoding.
Repository: localaiLicense: apache-2.0
underdog-saluki-27b-1.0-abliterated-mtp
Kujira's abliterated adaptation of Underdog Saluki 27B 1.0 uses mixed
IQ2 weights with an embedded MTP head. This text-only llama.cpp build
enables multi-token prediction with up to two draft tokens.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-uncensored
# Ornith-1.5-9B-uncensored
An **abliterated** (refusal-direction-ablated) build of
`ornith-ai/Ornith-1.5-9B`, produced with
ZeroFuse and published by
junafinity.
This is the **9B control checkpoint** (bf16). Mac users should start from the MLX-8bit or GGUF-8bit siblings. The official 9B base has **no `mtp.*` tensors**; nothing was grafted.
**Vision tower and MTP heads are preserved** — see
Vision & MTP preservation for the before/after audit.
## Intended use: red teaming and defensive cybersecurity research
These uncensored (abliterated) weights are built as a **research instrument** for red teaming and defensive cybersecurity work. Safety training suppresses the *display* of capability, not capability itself. A refusal tells you the model declined. It does not tell you whether the weights could have complied. That conflation underestimates the true ceiling and hides holes in *your* filters, classifiers, and policy layer.
Use each uncensored checkpoint as the **treatment half of a controlled pair** against its original base model:
...
Repository: localaiLicense: apache-2.0
qwen3.8-flash-next-uncensored
# Qwen3.8-Flash-Next
> [!Note]
> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.
> [!Tip]
> For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
>
> In particular, **Qwen3.8-Flash** is the official version based on Qwen3.8-Flash-Next with more production features, e.g., 1M context length by default, official built-in tools. For more information, please refer to the Qwen3.8-Flash Overview.
As the frontier of foundation models pushes toward ever-larger parameter counts and ever-longer context windows, the question is no longer just how much we can scale, but how efficiently we can do so. Sustainable progress toward artificial general intelligence (AGI) that benefits everyone demands architectural innovation. Today, we are sharing a concrete step in that direction: Qwen3.8-Flash-Next.
...
Repository: localaiLicense: apache-2.0
qwen3.8-27b-uncensored-hauhaucs-aggressive-mtp
# Qwen3.8-27B
> [!Note]
> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.
> [!Tip]
> For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
> In particular, **Qwen3.8-27B** will be available as a hosted version with more production features, e.g., 1M context length by default, official built-in tools. For more information, please refer to the Qwen3.8-27B Overview. The service is coming soon. Stay tuned for updates.
Following the widespread community adoption of the Qwen3.5 and Qwen3.6 series, we are pleased to introduce Qwen3.8, the most capable generation in the Qwen open-model family to date.
...
Repository: localaiLicense: apache-2.0
qwen3.8-27b-uncensored
# Qwen3.8-27B
> [!Note]
> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.
> [!Tip]
> For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
> In particular, **Qwen3.8-27B** will be available as a hosted version with more production features, e.g., 1M context length by default, official built-in tools. For more information, please refer to the Qwen3.8-27B Overview. The service is coming soon. Stay tuned for updates.
Following the widespread community adoption of the Qwen3.5 and Qwen3.6 series, we are pleased to introduce Qwen3.8, the most capable generation in the Qwen open-model family to date.
...
Repository: localaiLicense: apache-2.0
qwen3.8-27b-turbo-fable-cold-fusion-735-882-heretic-uncensored-neo-coder-max-mtp
RELEASE #1 GGUFS [including detailed notes, how to use, benches and much more]:
https://huggingface.co/DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF
Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NM-DAU (release #1, others pending...)
( repo has 10+ other versions (and 3 branches) noted below that EXCEED the performance of all QWEN 27B models, including fine tunes. )
First, special thanks to Nightmedia for working on the first three stages prior to heretic'ing/post staging and benching everything (3 sections below).
A number of my finetunes - both released and non-released - were used here as well as some third parties. Full details will be disclosed upon final release as the project shores up.
THREE example generations [snippets] from STAGE1-PART2, STAGE1b-PART2 and STAGE2-rplus2 at the bottom of the page.
Release(s) will be GGUFS first (linked here directly) then source code shortly thereafter [now released/open].
Some additional work and/ spawning of new branches from branch(es) below is still going on.
NEW: Branch 3 added, see below.
COMPLETED AND PENDING RELEASES:
...
Repository: localaiLicense: apache-2.0
qwen3.8-27b-uncensored-q4
Qwen3.8-27B-Uncensored reduces refusal behavior while retaining the base
model's text, vision, reasoning, and tool-use capabilities. Its integrated
MTP head supports speculative decoding without a separate draft model.
This default entry uses the Q4_K_M GGUF and F16 vision projector. A
higher-quality Q8_0 model is available as a variant.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-uncensored-q8
Qwen3.8-27B-Uncensored in the higher-quality Q8_0 GGUF format, with its
integrated MTP head and shared F16 vision projector.
Repository: localaiLicense: apache-2.0
qwen3.8-27b-heretic-abliterated-uncensored
# Qwen3.8-27B
> [!Note]
> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format.
>
> These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, TokenSpeed, etc.
> [!Tip]
> For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
> In particular, **Qwen3.8-27B** will be available as a hosted version with more production features, e.g., 1M context length by default, official built-in tools. For more information, please refer to the Qwen3.8-27B Overview. The service is coming soon. Stay tuned for updates.
Following the widespread community adoption of the Qwen3.5 and Qwen3.6 series, we are pleased to introduce Qwen3.8, the most capable generation in the Qwen open-model family to date.
...
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-uncensored-q4
Junafinity's Ornith-1.5-9B Uncensored is a 9B-parameter Qwen3.5
derivative with refusal-direction ablation for research and evaluation.
This Q4_K_M GGUF build includes the F16 vision projector and uses
the embedded chat template for text and image conversations.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-uncensored-q6
Junafinity's Ornith-1.5-9B Uncensored is a 9B-parameter Qwen3.5
derivative with refusal-direction ablation for research and evaluation.
This Q6_K GGUF build includes the F16 vision projector and uses
the embedded chat template for text and image conversations.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-uncensored-q8
Junafinity's Ornith-1.5-9B Uncensored is a 9B-parameter Qwen3.5
derivative with refusal-direction ablation for research and evaluation.
This Q8_0 GGUF build includes the F16 vision projector and uses
the embedded chat template for text and image conversations.
Repository: localaiLicense: apache-2.0
ornith-1.5-9b-obliterated-q4
Ornith-1.5-9B OBLITERATED is a refusal-removed derivative for alignment
research, red teaming, coding, reasoning, and agentic tasks. Its safety
guardrails are removed, and the publisher reports some capability loss
compared with the original model.
This default entry uses the Q4_K_M GGUF and BF16 vision projector. The
linked variant uses the higher-quality Q8_0 quantization.
Repository: localaiLicense: mit
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