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Source · Liquid AI

Liquid AI releases DSpark draft models for LFM2.5 to accelerate inference

Liquid AI has released draft model checkpoints for its LFM2.5 family—specifically LFM2.5-1.2B-Instruct, LFM2.5-2.6B, and LFM2.5-8B-A1B—that utilize speculative decoding to significantly improve inference speed without compromising output quality.

lab Liquid AI · 23d ago · 13 views

LFM2.5 Q4_0 checkpoints use Quantization-Aware Distillation to recover 97% of BF16 accuracy

The LFM2.5 team has released updated 4-bit GGUF checkpoints for the LFM2.5-230M, LFM2.5-350M, LFM2.5-1.2B-Instruct, and LFM2.5-2.6B models, trained using Quantization-Aware Distillation (QAD). This technique distills a high-precision teacher model into a quantized student to recover accuracy lost during standard quantization.