Raising Bars, Not Parameters: LilMoo Compact Language Model for Hindi

Researchers have developed LilMoo, a 0.6-billion parameter Hindi language model trained from scratch using a transparent, reproducible pipeline optimized for limited compute environments. The model outperforms similarly sized multilingual baselines like Qwen2.5-0.5B and Qwen3-0.6B, demonstrating that language-specific pretraining can rival larger multilingual models.