7M Parameters Beats Billion-Parameter Models: How Tiny Recursive Model Redefines Reasoning Efficiency

“ In an era where AI models are ballooning to trillions of parameters, a model smaller than two smartphone photos is defeating giants like DeepSeek-R1 and Gemini 2.5 Pro in the ARC-AGI challenge. “Is bigger always better?” This question has lingered in artificial intelligence for years. While major tech companies race to release increasingly larger models, Samsung SAIL Montreal’s Alexia Jolicoeur-Martineau took the opposite path. Her Tiny Recursive Model (TRM) uses just 7 million parameters—smaller than many image classification models—yet achieves 45% accuracy on ARC-AGI-1 and 8% on the more challenging ARC-AGI-2, outperforming competitors with thousands of times more parameters. …