Researchers at Hugging Face have demonstrated that small language models can outperform their larger counterparts using advanced test-time scaling methods. As reported by Ben Dickson for VentureBeat, a Llama 3 model with just 3 billion parameters matched the performance of its 70-billion-parameter version on complex mathematical tasks. The breakthrough relies on scaling “test-time compute,” which … Read more
Hugging Face has introduced SmolVLM, a new vision-language AI model that processes both images and text while using significantly less computing power than comparable solutions. As reported by Michael Nuñez, the model requires only 5.02 GB of GPU RAM, compared to competitors that need up to 13.70 GB. The system uses advanced compression technology to … Read more
Hugging Face has released SmolLM2, a new family of compact language models designed to run on smartphones and edge devices with limited processing power and memory. The models, released under the Apache 2.0 license, come in three sizes up to 1.7B parameters and achieve impressive performance on key benchmarks, outperforming larger models like Meta’s Llama … Read more
Hugging Face’s new ranking of the best freely avaiable language models shows that Chinese models currently lead the way. Alibaba’s Qwen models dominate the top spots in the ranking, which is based on more challenging tests than its predecessor. Skills such as knowledge recall, inferring from long texts, complex mathematics, and following instructions are assessed.