This model is the MLX format version of LiquidAI's LFM2-700M, a 700 million parameter language model converted for efficient inference on Apple Silicon using the MLX framework. LFM2 is a Liquid Foundation Model designed for edge deployment and supports multiple languages including English, Arabic, Chinese, French, German, Japanese, Korean, and Spanish. The 8-bit quantized version provides a balance between model performance and computational efficiency for text generation tasks.
LiquidAI
available local models on Mirai:
available local models on Mirai:
Name
Quantisation
Size
LFM2-1.2B
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-2.6B
uint8
2.6B
Quant.
uint8
Size
2.6B
LFM2-350M
uint8
350M
Quant.
uint8
Size
350M
LFM2-700M
uint8
700M
Quant.
uint8
Size
700M
LFM2.5-1.2B-Instruct
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Instruct-MLX-4bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Instruct-MLX-8bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Thinking
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-1.2B-4bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-1.2B-8bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-2.6B-4bit
uint8
2.6B
Quant.
uint8
Size
2.6B
LFM2-2.6B-8bit
uint8
2.6B
Quant.
uint8
Size
2.6B
LFM2-350M-4bit
uint8
350M
Quant.
uint8
Size
350M
LFM2-350M-8bit
uint8
350M
Quant.
uint8
Size
350M
LFM2-700M-4bit
uint8
700M
Quant.
uint8
Size
700M
LFM2-700M-8bit
uint8
700M
Quant.
uint8
Size
700M
LFM2.5-1.2B-Thinking-4bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Thinking-8bit
uint8
1.2B
Quant.
uint8
Size
1.2B
This model is the MLX format version of LiquidAI's LFM2-700M, a 700 million parameter language model converted for efficient inference on Apple Silicon using the MLX framework. LFM2 is a Liquid Foundation Model designed for edge deployment and supports multiple languages including English, Arabic, Chinese, French, German, Japanese, Korean, and Spanish. The 8-bit quantized version provides a balance between model performance and computational efficiency for text generation tasks.
LiquidAI
available local models on Mirai:
Name
Quantisation
Size
LFM2-1.2B
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-2.6B
uint8
2.6B
Quant.
uint8
Size
2.6B
LFM2-350M
uint8
350M
Quant.
uint8
Size
350M
LFM2-700M
uint8
700M
Quant.
uint8
Size
700M
LFM2.5-1.2B-Instruct
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Instruct-MLX-4bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Instruct-MLX-8bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Thinking
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-1.2B-4bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-1.2B-8bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2-2.6B-4bit
uint8
2.6B
Quant.
uint8
Size
2.6B
LFM2-2.6B-8bit
uint8
2.6B
Quant.
uint8
Size
2.6B
LFM2-350M-4bit
uint8
350M
Quant.
uint8
Size
350M
LFM2-350M-8bit
uint8
350M
Quant.
uint8
Size
350M
LFM2-700M-4bit
uint8
700M
Quant.
uint8
Size
700M
LFM2-700M-8bit
uint8
700M
Quant.
uint8
Size
700M
LFM2.5-1.2B-Thinking-4bit
uint8
1.2B
Quant.
uint8
Size
1.2B
LFM2.5-1.2B-Thinking-8bit
uint8
1.2B
Quant.
uint8
Size
1.2B