The fastest way to get this model running locally is via Optional Features.
Go through the configuration rules shown below.
The download manager will automatically pull several gigabytes of data.
The program scans your VRAM and RAM to seamlessly apply optimal configurations.
SmolLM3-3B is a compact language model designed for efficient inference on consumer hardware. It leverages a refined architecture that balances parameter count and context length, delivering strong performance in both reasoning and generation tasks. The model supports up to 8K tokens of context, enabling it to handle longer dialogues and documents without truncation. Benchmarks show it outperforms similarly sized models in multilingual understanding and code generation. Its training pipeline incorporates extensive data filtering and instruction tuning, resulting in coherent and factual outputs. The compact footprint makes it ideal for deployment in edge devices and research prototypes.
| Parameter | Value |
|---|---|
| Parameters | 3 B |
| Context Length | 8K tokens |
| Training Data | ≈1.5 TB filtered corpus |
| Inference Speed | ~120 tokens/s on GPU |
- Script automating visual encoder weight downloads for advanced multi-modal vision tasks
- Zero-Click Run SmolLM3-3B Windows 11 Local Guide Windows FREE
- Downloader pulling compact executive summary models for processing local file archives vaults
- SmolLM3-3B FREE
- Installer configuring distributed tensor calculation grids across multiple local computers
- Quick Run SmolLM3-3B FREE
- Downloader pulling translation models for offline multi-language translation
- How to Autostart SmolLM3-3B Quantized GGUF 2026/2027 Tutorial FREE