Hugging Face has launched SmolLM3, a new 3-billion-parameter language model designed for high performance and efficiency. In their official post, the company states that the model outperforms others in its size class and is competitive with some larger alternatives. A key feature is its dual-mode capability, which allows it to provide direct answers or show …
Hugging Face has developed an open-source version of autonomous research technology, matching key capabilities of OpenAI’s recently launched Deep Research feature. As reported by Benj Edwards for Ars Technica, the project called “Open Deep Research” was completed within 24 hours of OpenAI’s announcement. The new tool enables AI models to independently browse the web and …
Researchers at Hugging Face have launched a project to create an open-source version of DeepSeek’s R1 AI reasoning model. As reported by Kyle Wiggers for TechCrunch, the initiative called Open-R1 aims to duplicate all components of the original model, including training data and methods. Led by Hugging Face’s head of research Leandro von Werra, the …
Hugging Face has released two new AI models designed for processing images, videos, and text on devices with limited resources. As Kyle Wiggers reports for TechCrunch, the models called SmolVLM-256M and SmolVLM-500M require less than 1GB of RAM to operate. The models, containing 256 million and 500 million parameters respectively, can describe images, analyze video …
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 …
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 …
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 …
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.