Discover and install AI models from our curated collection
Repository: localaiLicense: other

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.
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Repository: localaiLicense: other

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.
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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.
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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.
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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.
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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.
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Repository: localaiLicense: other
AtomicChat's LFM2.5-24B-A2B derivative reduces refusal behavior in the original weights. This text-only mixture-of-experts model has 24B total parameters and supports multilingual reasoning and tool use. This entry uses the AD-Q4_K_M GGUF build with the edits baked in.
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Repository: localaiLicense: other
AtomicChat's LFM2.5-24B-A2B derivative reduces refusal behavior in the original weights. This text-only mixture-of-experts model has 24B total parameters and supports multilingual reasoning and tool use. This entry uses the AD-Q6_K GGUF build with the edits baked in.
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Repository: localaiLicense: other
AtomicChat's LFM2.5-24B-A2B derivative reduces refusal behavior in the original weights. This text-only mixture-of-experts model has 24B total parameters and supports multilingual reasoning and tool use. This entry uses the AD-Q8_0 GGUF build with the edits baked in.
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Repository: localaiLicense: apache-2.0
LLM-jp-4-33B-thinking is an Apache-2.0 Japanese and English reasoning model from Japan's National Institute of Informatics. Its dense Llama architecture has 33 billion parameters and a 65K-token context window. The model was aligned with supervised fine-tuning and DPO for multi-turn conversation and instruction following. This default entry uses the 20.2 GB Q4_K_M GGUF. The official 66.4 GB BF16 weights are available as a higher-fidelity variant.
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LLM-jp-4-33B-thinking in the official 66.4 GB BF16 GGUF format. This variant preserves the original model precision for hosts with enough memory.
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Repository: localaiLicense: apache-2.0
WeMM-Embedding-2B is Tencent's Apache-2.0 multilingual embedding model built on Qwen3.5. This entry serves the original bfloat16 safetensors with LocalAI's Transformers backend and produces 2,048-dimensional normalized embeddings for text retrieval, semantic search, and RAG. The upstream model can also embed images and videos. LocalAI currently exposes text input through its embeddings API for this backend.
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Repository: localaiLicense: apache-2.0
WeMM-Embedding-4B is Tencent's mid-sized Apache-2.0 multilingual embedding model built on Qwen3.5. This entry serves the original bfloat16 safetensors with LocalAI's Transformers backend and produces 2,560-dimensional normalized embeddings for text retrieval, semantic search, and RAG. The upstream model can also embed images and videos. LocalAI currently exposes text input through its embeddings API for this backend.
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Repository: localaiLicense: apache-2.0
WeMM-Embedding-9B is Tencent's largest Apache-2.0 multilingual embedding model built on Qwen3.5. This entry serves the original bfloat16 safetensors with LocalAI's Transformers backend and produces 4,096-dimensional normalized embeddings for text retrieval, semantic search, and RAG. The upstream model can also embed images and videos. LocalAI currently exposes text input through its embeddings API for this backend.
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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: apache-2.0
Hy-MT2-7B is Tencent's 7B multilingual translation model. It supports translation instructions across 33 languages, including terminology control and style transfer. This Q4_K_M GGUF uses the embedded chat template with an 8K context window. Include the target language in your prompt.
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