Intern S1 mini 💻Github Repo • 🤗Model Collections • 📜Technical Report • 🏠Project Page 👋 join us on Discord and WeChat Introduction We introduce Intern S1 mini , a lightweight open source multimodal reasoning model based on the same techniques as Intern S1 . Built upon an 8B dense language model (Qwen3) and a 0.3B Vision encoder (InternViT), Intern S1 mini has been further pretrained on 5 trillion tokens of multimodal data, including over 2.5 trillion scientific domain tokens . This enables the model to retain strong general capabilities while excelling in specialized scientific domains such as interpreting chemical structures, understanding protein sequences, and planning compound synthesis routes , making Intern S1 mini to be a capable research assistant for real world scientific applications. Features Strong performance across language and vision reasoning benchmarks, especially scientific tasks. Continuously pretrained on a massive 5T token dataset, with over 50% specialized scientific data, embedding deep domain expertise. Dynamic tokenizer enables native understanding of molecular formulas and protein sequences. Performance We evaluate the Intern S1 mini on various…
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