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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

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

qwen3.8-9b-q8
Qwen3.8-9B in the higher-quality Q8_0 GGUF format. This variant preserves more model fidelity for hosts with enough memory.

Repository: localaiLicense: apache-2.0

qwen3.8-4b-q4
Qwen3.8-4B is Empero AI's full-parameter distillation of Qwen3.8 2.4T A95B into the Qwen3.5-4B architecture. It targets mathematics, reasoning, instruction following, and tool use with 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

qwen3.8-4b-q8
Qwen3.8-4B in the higher-quality Q8_0 GGUF format. This variant preserves more model fidelity for hosts with enough memory.

Repository: localaiLicense: apache-2.0

qwen3.8-2b-q4
Qwen3.8-2B is Empero AI's smallest Qwen3.8 reasoning distillation. It uses the Qwen3.5-2B architecture and targets mathematics, instruction following, tool use, and edge deployment with 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

qwen3.8-2b-q8
Qwen3.8-2B in the higher-quality Q8_0 GGUF format. This variant preserves more model fidelity while remaining suitable for compact hosts.

Repository: localaiLicense: apache-2.0

qwen3.5-9b-defiant-fable-mtp
Qwen3.5 9B Defiant Fable is an Apache-2.0 multimodal fine-tune for reasoning, coding, creative writing, and roleplay. It retains the 256K context window and vision support of Qwen3.5 while reducing refusals. This default entry uses the NEO-imatrix Q4_K_M build with multi-token prediction enabled for faster generation.

Repository: localaiLicense: apache-2.0

qwen3.5-9b-defiant-fable
Qwen3.5 9B Defiant Fable in the plain NEO-imatrix Q4_K_M GGUF format. This fallback offers the same multimodal reasoning, coding, and creative capabilities without enabling multi-token prediction.

Repository: localaiLicense: apache-2.0

btl-4-compact
BTL-4 Compact is Bad Theory Labs' text-only 35B mixture-of-experts model compressed into a single 9.96 GB IQ2_XXS GGUF. Around 2.1B parameters are active per token, and the model is tuned for agentic work, tool use, coding, and reasoning. The compact build omits the vision tower and disables the source model's MTP layer for compatibility with stock llama.cpp.

Repository: localaiLicense: apache-2.0

parable-qwen3-4b-claude-fable-5
# Parable-Qwen3-4B-Claude-Fable-5 Qwen3 4B fine-tuned on genuine Claude Fable 5 agent traces. Thinking-mode reasoning, agent/terminal task flavor, tool-call formatting.

Repository: localaiLicense: apache-2.0

parable-qwen3-8b-claude-fable-5
# Parable-Qwen3-8B-Claude-Fable-5 Qwen3 8B fine-tuned on genuine Claude Fable 5 agent traces. Thinking-mode reasoning with agent/terminal flavor and tool-call formatting.

Repository: localaiLicense: apache-2.0

qwen3.6-35b-a3b-uncensored-genesis-hermes-v6
Qwen3.6-35B-A3B Uncensored Genesis Hermes V6 is LuffyTheFox's multimodal, agentic derivative of HauhauCS's uncensored Qwen3.6-35B-A3B model. It combines Genesis tensor calibration with Hermes function-calling data while retaining the 35B mixture-of-experts architecture, roughly 3B active parameters per token, and the native 262K-token context window. This entry installs the Q8_0 GGUF together with its F16 multimodal projector for llama.cpp. The model card recommends Jinja chat templates and at least a 128K context for its thinking behavior. License: Apache-2.0.

Repository: localaiLicense: apache-2.0

qwen3.6-35b-a3b-genesis-hermes-v7
Qwen3.6-35B-A3B Genesis Hermes V7 is LuffyTheFox's Apache-2.0 multimodal, agentic derivative of HauhauCS's uncensored Qwen3.6-35B-A3B model. It combines Genesis tensor calibration with Hermes function-calling data while retaining the 35B mixture-of-experts architecture, roughly 3B active parameters per token, and the native 262K-token context window. This entry's own payload uses the model card's recommended APEX GGUF and the shared F16 multimodal projector. Automatic variant selection may instead choose Compact APEX, an MTP-enabled APEX build, or Q8_K_P based on serving features and available memory. The model card recommends Jinja chat templates and at least a 128K context for its thinking behavior.

Repository: localaiLicense: apache-2.0

qwen3.6-35b-a3b-genesis-hermes-v7-apex-compact
Qwen3.6-35B-A3B Genesis Hermes V7 in the smaller APEX Compact GGUF format, with the shared F16 multimodal projector. This build preserves the model's multimodal, reasoning, coding, and agentic capabilities for hosts with less memory than the recommended full APEX build.

Repository: localaiLicense: apache-2.0

qwen3.6-35b-a3b-genesis-hermes-v7-mtp-apex
Qwen3.6-35B-A3B Genesis Hermes V7 in the full APEX GGUF format with native multi-token prediction enabled for speculative decoding, plus the shared F16 multimodal projector.

Repository: localaiLicense: apache-2.0

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