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qwen3.8-27b-dflash2
# 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

huihui-qwen3.8-27b-abliterated
# 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-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-1.0-9b-q4
Ornith-1.0-9B is an MIT-licensed Qwen3.5 model from Ornith AI for agentic coding, reasoning, repository-level software tasks, and tool use. It supports text and image input with a context window of 262K tokens. 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: mit

ornith-1.0-9b-q8
Ornith-1.0-9B in the higher-quality Q8_0 GGUF format, with the shared F16 vision projector for multimodal prompts.

Repository: localaiLicense: mit

ornith-1.5-9b-q4
Ornith-1.5-9B is an MIT-licensed Qwen3.5 model from Ornith AI for agentic coding, reasoning, repository-level software tasks, and tool use. It supports text and image input with a context window of 262K tokens. This default entry uses the Q4_K_M GGUF and BF16 vision projector. A higher-quality Q8_0 model is available as a variant.

Repository: localaiLicense: mit

ornith-1.5-9b-q8
Ornith-1.5-9B in the higher-quality Q8_0 GGUF format, with the shared BF16 vision projector for multimodal prompts.

Repository: localaiLicense: mit

ornith-1.5-35b-a3b-q4
Ornith-1.5-35B-A3B is an MIT-licensed Qwen3.5 mixture-of-experts model from Ornith AI for agentic coding, reasoning, repository-level software tasks, and tool use. It activates about 3B parameters per token and supports text and image input with a context window of 262K tokens. This default entry uses the Q4_K_M GGUF and BF16 vision projector. A higher-quality Q8_0 model is available as a variant.

Repository: localaiLicense: mit

ornith-1.5-35b-a3b-q8
Ornith-1.5-35B-A3B in the higher-quality Q8_0 GGUF format, with the shared BF16 vision projector for multimodal prompts.

Repository: localaiLicense: mit

tiel-coder-35b-a3b-q4
Tiel-Coder-35B-A3B is a 35B-parameter mixture-of-experts model for coding, reasoning, tool use, and vision tasks. This default entry uses the Q4_K_XL GGUF and BF16 vision projector.

Repository: localaiLicense: mit

tiel-coder-35b-a3b-q4-mtp
Tiel-Coder-35B-A3B in Q4_K_XL format with MTP speculative decoding and a BF16 vision projector.

Repository: localaiLicense: mit

tiel-coder-35b-a3b-q8
Tiel-Coder-35B-A3B in the higher-quality Q8_K_XL GGUF format, with the BF16 vision projector for multimodal prompts.

Repository: localaiLicense: mit

ornith-1.5-397b-q4
Ornith-1.5-397B is Ornith AI's MIT-licensed flagship mixture-of-experts model for agentic coding, reasoning, repository-level tasks, and tool use. It supports text and image input with a context window of 262K tokens. This default entry uses the Q4_K_M GGUF and BF16 vision projector. A higher-quality Q8_0 model is available as a variant.

Repository: localaiLicense: mit

ornith-1.5-397b-q8
Ornith-1.5-397B in the higher-quality Q8_0 GGUF format, with the shared BF16 vision projector for multimodal prompts.

Repository: localaiLicense: mit

qwen3.8-27b-obliterated-q4
Qwen3.8-27B OBLITERATED is an Apache-2.0 Qwen3.8 vision-language model modified for refusal-removal and red-team research. It retains reasoning, coding, tool use, image, and video capabilities, but its safety guardrails have been removed. This default entry uses the Q4_K_M GGUF and BF16 vision projector. The linked variant uses the higher-quality Q8_0 model. The publisher recommends greedy decoding with a 1.15 repetition penalty.

Repository: localaiLicense: apache-2.0

qwen3.8-27b-obliterated-q8
Qwen3.8-27B OBLITERATED in the higher-quality Q8_0 GGUF format. This model is modified for refusal-removal and red-team research, and its safety guardrails have been removed.

Repository: localaiLicense: apache-2.0

qwen3.8-27b-q4
Qwen3.8-27B is Qwen's dense 27B vision-language model for reasoning, coding, tool use, and long-running agent tasks. It accepts text, images, and video, and it supports a native context window of 262K tokens. This default entry uses the official Q4_K_M GGUF and Q8_0 vision projector. The linked variants add MTP speculative decoding or use the higher-quality Q8_0 model.

Repository: localaiLicense: apache-2.0

qwen3.8-27b-q4-mtp
Qwen3.8-27B with the official Q4_K_M model and Q4_0 MTP draft model. MTP speculative decoding can increase generation speed by proposing multiple tokens for the target model to verify.

Repository: localaiLicense: apache-2.0

qwen3.8-27b-q8
Qwen3.8-27B in the official Q8_0 GGUF format. This variant provides higher model fidelity for hosts with enough memory.

Repository: localaiLicense: apache-2.0

qwen3.8-27b-ridge
Qwen3.8-27B Ridge is a 3.69-bit mixed quantization that keeps the Gated-DeltaNet state path at Q8_0 and preserves the embedded MTP head. It reduces the model weights to 12.59 GB while retaining multimodal, reasoning, coding, tool-use, and long-context capabilities.

Repository: localaiLicense: apache-2.0

qwen3.8-9b-q4
Qwen3.8-9B is Empero AI's full-parameter distillation of Qwen3.8 2.4T A95B into the dense Qwen3.5-9B architecture. It targets reasoning, mathematics, coding, instruction following, and tool use, and supports a native 262K-token context window. This default entry uses Q4_K_M weights; a higher-quality Q8_0 build is available as a variant.

Repository: localaiLicense: apache-2.0

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