From the model card
Fields below are copied from the tags and counters on the HuggingFace repository HuggingFaceTB/SmolLM3-3B at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- HuggingFaceTB
- Pipeline tag
- text-generation
- Library
- Transformers
- Weight formats
- safetensors
- License tag
apache-2.0— read the license file in the repo before relying on it- Lineage
-
- base model HuggingFaceTB/SmolLM3-3B-Base
- fine-tune of HuggingFaceTB/SmolLM3-3B-Base
- Language tags
- English (en), French (fr), Spanish (es), Italian (it), Portuguese (pt), Chinese (zh), Arabic (ar), Russian (ru)
- Downloads (HF counter at last fetch)
- 564,000
- Likes (HF counter at last fetch)
- 1,021
- Model card
- https://huggingface.co/HuggingFaceTB/SmolLM3-3B
Use cases
- On-device inference on smartphones or edge hardware within VRAM budget
- Multilingual chatbot and assistant applications at low cost
- RAG text generation in latency-sensitive pipelines
- Fine-tuning base for domain-specific instruction following
- Offline AI assistant in bandwidth-limited environments
Pros
- 3B scale runs on consumer GPU (6GB VRAM) or accelerated mobile hardware
- Apache-2.0 licensed for open commercial use
- 8-language support without separate per-language models
- HuggingFace-maintained model with active upstream support
Cons
- 3B parameters have clear quality ceiling on complex multi-step reasoning tasks
- Multilingual quality is uneven — English and Chinese are typically strongest
- No native tool-calling or function-calling support without custom tuning
- Context window length and exact tokenizer need verification for edge deployment targets
Tags
transformerssafetensorssmollm3text-generationconversationalenfresitptzharrubase_model:HuggingFaceTB/SmolLM3-3B-Basebase_model:finetune:HuggingFaceTB/SmolLM3-3B-Baselicense:apache-2.0endpoints_compatibleregion:usdeploy:azure