IBM Granite 4.2 3B is a compact multilingual reasoning model for chat, coding, long-context tasks, and tool use. This entry uses the Q4_K_M GGUF; a higher-fidelity Q8_0 build is available as a variant.
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IBM Granite 4.2 3B in the higher-fidelity Q8_0 GGUF format. It is a compact multilingual reasoning model for chat, coding, and tool use.
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IBM Granite 4.2 8B is a multilingual reasoning model for chat, coding, long-context tasks, and tool use. This entry uses the Q4_K_M GGUF; a higher-fidelity Q8_0 build is available as a variant.
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IBM Granite 4.2 8B in the higher-fidelity Q8_0 GGUF format. It is a multilingual reasoning model for chat, coding, and tool use.
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IBM Granite 4.2 30B is the family's flagship multilingual reasoning model for chat, coding, long-context tasks, and tool use. This entry uses the Q4_K_M GGUF; a higher-fidelity Q8_0 build is available as a variant.
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IBM Granite 4.2 30B in the higher-fidelity Q8_0 GGUF format. It is the family's flagship multilingual reasoning model for chat, coding, and tool use.
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Repository: localaiLicense: mit
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.
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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.
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Repository: localaiLicense: mit
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.
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Ornith-1.0-9B in the higher-quality Q8_0 GGUF format, with the shared F16 vision projector for multimodal prompts.
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Repository: localaiLicense: mit
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.
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Ornith-1.5-9B in the higher-quality Q8_0 GGUF format, with the shared BF16 vision projector for multimodal prompts.
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Repository: localaiLicense: mit
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.
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Ornith-1.5-35B-A3B in the higher-quality Q8_0 GGUF format, with the shared BF16 vision projector for multimodal prompts.
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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.
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Tiel-Coder-35B-A3B in Q4_K_XL format with MTP speculative decoding and a BF16 vision projector.
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Tiel-Coder-35B-A3B in the higher-quality Q8_K_XL GGUF format, with the BF16 vision projector for multimodal prompts.
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Repository: localaiLicense: mit
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.
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Ornith-1.5-397B in the higher-quality Q8_0 GGUF format, with the shared BF16 vision projector for multimodal prompts.
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Repository: localaiLicense: apache-2.0

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.
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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.
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