Post-Training Quantization

Taobao's MNN team trained from scratch and open-sourced MNN-Pocket-0.3B, a ~300M-parameter on-device language model co-optimized across architecture, tokenizer, training data, post-training and quantized inference, shipping as a 173MB INT4 package. Running fully offline via the MNN engine, it reaches roughly 350 tokens/s decode on iPhone 18 Pro and adds about 228MB peak Metal residency on iPad Pro M5, with a speculative-decoding draft model delivering up to 2.06x speedup.