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ling-3.0-flash-iq1
Ling-3.0-flash is InclusionAI's MIT-licensed hybrid reasoning MoE model with 124B total parameters and 5.5B active parameters per token. It targets coding, deep research, instruction following, and agentic workflows with a native 256K-token context window. This default entry uses the 36.5 GB AD-IQ1_M GGUF. A higher-quality 44.7 GB AD-IQ2_XS model is available as a variant.

Repository: localaiLicense: mit

ling-3.0-flash-iq2
Ling-3.0-flash in the higher-quality 44.7 GB AD-IQ2_XS GGUF format. This variant preserves more model fidelity for hosts with enough memory.

Repository: localaiLicense: mit

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

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

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