LFM2.5 8B A1B Alternatives

LFM2-1.2B is a 1.2 billion parameter model developed by Liquid AI. It features a custom chat template supporting tool lists and system prompts. The model is designed for efficient local or cloud inference and is suitable for conversational AI and agentic applications.

LFM2.5-1.2B-Instruct is a 1.2 billion parameter language model from LiquidAI, optimized for instruction following and conversational tasks. It includes a chat template and supports tool use. The model is distributed on Hugging Face and can be run locally or via inference providers using the Transformers library. It is suitable for on-device or resource-constrained applications requiring capable language understanding.

LFM2.5-1.2B is a compact 1.2 billion parameter instruct model from LiquidAI, distributed in GGUF format for easy use with llama.cpp and other local inference engines. It is designed for efficient on-device or CPU-based text generation and instruction following. The model balances performance and resource usage for local deployment scenarios.

LFM2.5-VL-1.6B-GGUF is a quantized GGUF version of Liquid AI's 1.6 billion parameter vision-language foundation model. It supports multimodal inputs including images and text, with a chat template optimized for local execution using tools like llama.cpp. Designed for efficient on-device or local server inference without requiring high-end GPUs.

This is a quantized (5-bit) version of the LFM2-24B model in MLX format, suitable for efficient inference on Apple devices. It includes a chat template and is distributed via Hugging Face for use with MLX and related tools.

This is a quantized (6-bit) version of the LFM2-24B model in MLX format, suitable for efficient inference on Apple devices. It includes a chat template and is distributed via Hugging Face for use with MLX and related tools.

LFM2.5-1.2B-Instruct-MLX-6bit is a 6-bit quantized version of a 1.2 billion parameter instruction-tuned language model optimized for the MLX framework on Apple silicon. It includes a chat template and supports tool use. The model is distributed on Hugging Face for local inference on Macs and is suitable for developers seeking lightweight on-device AI capabilities.

LFM2.5-1.2B-Instruct-MLX-8bit is a small instruction-tuned language model provided in an 8-bit quantized format optimized for the MLX framework on Apple devices. It supports tool use and system prompts. The model is hosted on Hugging Face for easy integration into local AI applications and experimentation.

This repository hosts an 8-bit quantized MLX version of the LFM2-24B model optimized for Apple Silicon. It includes a custom chat template with system prompt and tool support. The model is designed for local inference on Macs using the MLX framework and is distributed via Hugging Face.

This is a 4-bit quantized version of the LFM2-24B model using the MLX framework, optimized for Apple silicon devices. Hosted by the LM Studio community, it enables efficient local inference of a large language model on Macs. The model includes a comprehensive chat template supporting tools and system prompts.

A 4-bit quantized version of the LFM2.5 1.2B Instruct model optimized for the MLX framework on Apple Silicon. It is designed for local inference on Macs and includes a chat template suitable for instruction following. The model is distributed via Hugging Face for use with MLX and LM Studio.