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sage-a1.5-q4
Sage-A1.5 is a 35B mixture-of-experts model based on Qwen3.6 for scientific reasoning, coding, and tool use. This official Q4_K_M GGUF build uses llama.cpp and includes the vision projector.

Repository: localaiLicense: apache-2.0

sage-a1.5-q8
Sage-A1.5 is a 35B mixture-of-experts model based on Qwen3.6 for scientific reasoning, coding, and tool use. This official Q8_0 GGUF build uses llama.cpp and includes the vision projector.

Repository: localaiLicense: apache-2.0

lfm2.5-24b-a2b-turbo-brilliance-iq4-xs
DavidAU's Turbo Brilliance build of LFM2.5-24B-A2B, a text-only reasoning model with 24B total parameters and 2.45B active parameters. This entry uses the IQ4_XS GGUF quantization and the embedded Turbo Brilliance chat template for multilingual chat and tool use.

Repository: localaiLicense: other

lfm2.5-24b-a2b-turbo-brilliance-q8
DavidAU's Turbo Brilliance build of LFM2.5-24B-A2B, a text-only reasoning model with 24B total parameters and 2.45B active parameters. This entry uses the Q8_0 MAX GGUF quantization and the embedded Turbo Brilliance chat template for multilingual chat and tool use.

Repository: localaiLicense: other

tess-4.5-27b-q4
Tess 4.5 is a 27B Qwen3.8 fine-tune for coding, reasoning, and tool use. This Q4_K_M GGUF build includes the F16 vision projector and uses llama.cpp with the embedded chat template. Speculative decoding is disabled.

Repository: localaiLicense: apache-2.0

tess-4.5-27b-q6
Tess 4.5 is a 27B Qwen3.8 fine-tune for coding, reasoning, and tool use. This Q6_K GGUF build includes the F16 vision projector and uses llama.cpp with the embedded chat template. Speculative decoding is disabled.

Repository: localaiLicense: apache-2.0

tess-4.5-27b-q8
Tess 4.5 is a 27B Qwen3.8 fine-tune for coding, reasoning, and tool use. This Q8_0 GGUF build includes the F16 vision projector and uses llama.cpp with the embedded chat template. Speculative decoding is disabled.

Repository: localaiLicense: apache-2.0

spark-x2.6-4b-q4
Spark-X2.6-4B is XHToken's 4B text model for conversation, reasoning, coding, and multilingual tasks. This build uses Q4_K_M GGUF weights, the embedded Jinja chat template, and a 32K-token default context.

Repository: localaiLicense: apache-2.0

spark-x2.6-4b-q8
Spark-X2.6-4B is XHToken's 4B text model for conversation, reasoning, coding, and multilingual tasks. This build uses Q8_0 GGUF weights, the embedded Jinja chat template, and a 32K-token default context.

Repository: localaiLicense: apache-2.0

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

ornith-1.5-122b-ud-q4-k-xl
Ornith 1.5 122B is a Qwen3.5 mixture-of-experts model for reasoning, coding, and tool use. This UD-Q4_K_XL GGUF build includes the F16 vision projector for image input and uses an 8,192-token default context.

Repository: localaiLicense: mit

ornith-1.5-122b-q8
Ornith 1.5 122B is a Qwen3.5 mixture-of-experts model for reasoning, coding, and tool use. This Q8_0 GGUF build includes the F16 vision projector for image input and uses an 8,192-token default context.

Repository: localaiLicense: mit

humanizer-12b-bf16
Humanizer is a 12B Gemma 4 fine-tune for rewriting English and Chinese text. This unquantized BF16 GGUF build uses llama.cpp with an 8,192-token context. This entry uses the completions API with the publisher's exact rewriting prompt.

Repository: localaiLicense: apache-2.0

lfm2.5-24b-a2b-ud-q4
LiquidAI LFM2.5-24B-A2B is a text-only reasoning model with 24B total parameters and 2.45B active parameters for multilingual chat and tool use. This entry uses Unsloth's dynamic UD-Q4_K_XL GGUF quantization.

Repository: localaiLicense: other

lfm2.5-24b-a2b-ud-q6
LiquidAI LFM2.5-24B-A2B is a text-only reasoning model with 24B total parameters and 2.45B active parameters for multilingual chat and tool use. This entry uses Unsloth's dynamic UD-Q6_K_XL GGUF quantization.

Repository: localaiLicense: other

bge-large-en-v1.5-f16
BGE-large-en-v1.5 is a 335M English embedding model for semantic search and retrieval. This F16 GGUF build produces 1024-dimensional embeddings with a 512-token context. For retrieval, prefix queries with "Represent this sentence for searching relevant passages: "; leave passages unprefixed.

Repository: localaiLicense: mit

bge-large-en-v1.5-q8-0
BGE-large-en-v1.5 is a 335M English embedding model for semantic search and retrieval. This Q8_0 GGUF build produces 1024-dimensional embeddings with a 512-token context. For retrieval, prefix queries with "Represent this sentence for searching relevant passages: "; leave passages unprefixed.

Repository: localaiLicense: mit

bge-large-en-v1.5-q4-k-m
BGE-large-en-v1.5 is a 335M English embedding model for semantic search and retrieval. This Q4_K_M GGUF build produces 1024-dimensional embeddings with a 512-token context. For retrieval, prefix queries with "Represent this sentence for searching relevant passages: "; leave passages unprefixed.

Repository: localaiLicense: mit

bge-large-en-v1.5-transformers
BGE-large-en-v1.5 is a 335M English embedding model for semantic search and retrieval. This safetensors build uses the Transformers backend's SentenceTransformer loader, producing 1024-dimensional embeddings with a 512-token context. For retrieval, prefix queries with "Represent this sentence for searching relevant passages: "; leave passages unprefixed.

Repository: localaiLicense: mit

bge-base-en-v1.5-f16
BGE-base-en-v1.5 is a 109M English embedding model for semantic search and retrieval. This F16 GGUF build produces 768-dimensional embeddings with a 512-token context. For retrieval, prefix queries with "Represent this sentence for searching relevant passages: "; leave passages unprefixed.

Repository: localaiLicense: mit

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