Repository: localaiLicense: other

LFM2.5-2.6B is LiquidAI's compact, text-only reasoning model for on-device agentic workloads. It has 2.69B parameters, a 128K-token context window, multilingual support, and post-training for tool use, instruction following, data extraction, RAG, and multi-step agents. This entry uses the recommended Q4_K_M GGUF quantization from LiquidAI's official repository.
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Repository: localaiLicense: other

LFM2.5-2.6B is LiquidAI's compact, text-only reasoning model for on-device agentic workloads. It has 2.69B parameters, a 128K-token context window, multilingual support, and post-training for tool use, instruction following, data extraction, RAG, and multi-step agents. This entry uses the higher-quality Q8_0 GGUF quantization from LiquidAI's official repository.
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Repository: localaiLicense: other

LFM2.5-2.6B with LiquidAI's DSpark speculative drafter. This build pairs the Q4_K_M target with the compact Q4_K_M draft sidecar for lower-memory hosts. DSpark proposes blocks of tokens that the target model verifies, which preserves the target model's output while accelerating generation.
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Repository: localaiLicense: other

LFM2.5-2.6B with LiquidAI's DSpark speculative drafter. This build pairs the higher-quality Q8_0 target with the recommended F16 draft sidecar for the best acceptance length. DSpark proposes blocks of tokens that the target model verifies, which preserves the target model's output while accelerating generation.
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Repository: localai
This is a large language model (2.6B parameters) designed for text-generation tasks. It is a quantized version of the original model `LiquidAI/LFM2-2.6B-Transcript`, optimized for efficiency while retaining strong performance. The model is built on the foundation of the base model, with additional optimizations for deployment and use cases like transcription or language modeling. It is trained on large-scale text data and supports multiple languages.
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