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SmolVLM is a 2B parameter vision-language model (VLM) that achieves state-of-the-art performance for its memory footprint, offering a small, fast, and memory-efficient solution for multimodal tasks. It is fully open-source, with all model checkpoints, datasets, training recipes, and tools released under the Apache 2.0 license, enabling local deployment, reduced inference costs, and user customization.