Qwen1.5-MoE: Matching 7B Model Performance with 1/3 Activated Parameters
GitHub Pages 2 years ago 53
Alibaba's Qwen team released Qwen1.5-MoE-A2.7B, a mixture-of-experts language model with 2.7 billion activated parameters that matches the performance of 7-billion-parameter models like Mistral 7B and Qwen 1.5-7B on benchmarks including MMLU, GSM8K, and HumanEval. The model reduces training costs by 75% and achieves 1.74 times faster inference speed compared to the standard Qwen 1.5-7B, while using only one-third of the non-embedding parameters. The efficiency gains enable practitioners to deploy comparable model quality with substantially lower computational requirements for both training and inference.