SmolLM2 1.7B

SmolLM2 1.7B is Hugging Face's compact language model designed for on-device and edge deployment. Trained on 11 trillion tokens from a diverse mix of web data, code, and mathematics datasets, it delivers surprisingly strong performance for its size. Despite being one of the smallest models available, SmolLM2 1.7B outperforms other models in its class on reasoning, knowledge, and instruction-following tasks. Its tiny VRAM footprint makes it ideal for resource-constrained environments where larger models are impractical.