Samsung researchers have unveiled a breakthrough AI model called Tiny Recursive Model (TRM) — a system that’s about 10,000× smaller than massive models like DeepSeek and Gemini 2.5 Pro, yet beats them on advanced reasoning benchmarks like ARC-AGI 1 and 2.
How It Works
Instead of just predicting text like standard LLMs, TRM thinks recursively.
It drafts an answer, then builds a hidden “scratchpad” for reasoning — repeatedly critiquing and refining its logic up to 16 times before finalizing the answer.
This recursive loop allows the model to solve complex, puzzle-like problems with only 7 million parameters, achieving 45% test accuracy on ARC-AGI 1 and 8% on ARC-AGI 2, outperforming much larger systems.
Why It Matters
TRM shows that architecture and reasoning loops, not just model size, are key to intelligence.
It proves that small, efficient networks can rival frontier AI models while being cheaper to train and deploy — validating neuro-symbolic ideas about how reasoning can emerge from compact systems.
The result: a major step toward smarter, faster, and more accessible AI for real-world use.
