SmolLM3 Table of Contents 1. Model Summary 2. How to use 3. Evaluation 4. Training 5. Limitations 6. License Model Summary SmolLM3 is a 3B parameter language model designed to push the boundaries of small models. It supports dual mode reasoning, 6 languages and long context. SmolLM3 is a fully open model that offers strong performance at the 3B–4B scale. The model is a decoder only transformer using GQA and NoPE (with 3:1 ratio), it was pretrained on 11.2T tokens with a staged curriculum of web, code, math and reasoning data. Post training included midtraining on 140B reasoning tokens followed by supervised fine tuning and alignment via Anchored Preference Optimization (APO). Key features Instruct model optimized for hybrid reasoning Fully open model : open weights + full training details including public data mixture and training configs Long context: Trained on 64k context and supports up to 128k tokens using YARN extrapolation Multilingual : 6 natively supported (English, French, Spanish, German, Italian, and Portuguese) For more details refer to our blog post: https://hf.co/blog/smollm3 How to use The modeling code for SmolLM3 is available in transformers v4.53.0 , so make sure…
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