Hugging Face today has released SmolLM2, a new family of compact language models that achieve impressive performance while requiring far fewer computational resources than their larger counterparts. The new models, released under the Apache 2.0 license, come in three sizes — 135M, 360M and 1.7B parameters — making them suitable for deployment on smartphones and other edge devices where processing power and memory are limited. Most notably, the 1.7B parameter version outperforms Meta’s Llama 1B model on several key benchmarks. “SmolLM2 demonstrates significant advances over its predecessor, particularly in instruction following, knowledge, reasoning and mathematics,” according to Hugging Face’s model documentation. The largest variant was trained on 11 trillion tokens using a diverse dataset combination including FineWeb-Edu and specialized mathematics and coding datasets. This development comes at a crucial time when the AI industry is grappling with the computational demands of running large language models (LLMs). While companies like OpenAI and Anthropic push the boundaries with increasingly massive models, there’s growing recognition of the need for efficient, lightweight AI that can run locally on devices. The push for bigger AI models has left many potential users behind. Running these models requires expensive cloud computing services, which come with their own problems: slow response times, data privacy risks and high costs that small companies and independent developers simply can’t afford. SmolLM2 offers a different approach by bringing powerful AI capabilities directly to personal devices, pointing toward a future where advanced AI tools are within reach of more users and companies, not just tech giants with massive data centers.

Full report : Hugging Face’s open source small language model, SmolLM2 aims to bring generative AI to your smartphone.