Install SmolLM3-3B Using Pinokio
The fastest way to get this model running locally is via Optional Features.
Check out the detailed setup guide below to begin.
The framework seamlessly downloads the massive neural network binaries.
To save you time, the system will automatically determine efficient resource allocation.
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 |
- Downloader pulling enhanced voice profiles for local Fish-Speech voiceover workflows
- Full Deployment SmolLM3-3B 100% Private PC For Low VRAM (6GB/8GB) Local Guide Windows FREE
- Script downloading specialized math-reasoning models for offline calculators
- SmolLM3-3B FREE
- Installer configuring localized guardrail classification models for input-output automated filtering layers
- Launch SmolLM3-3B Locally via LM Studio Quantized GGUF Easy Build FREE
