SmolLM3-3B on Your PC with Native FP4

A standalone PowerShell module provides the fastest route to local installation.

Kindly follow the on-screen instructions below.

An automated background process downloads all required large-scale files.

The configuration wizard runs silently to set up the model for peak performance.

📤 Release Hash: 918f0110262856049176b9caa8e7a75d • 📅 Date: 2026-06-24 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: enough space for background apps and OS overhead Disk Space: at least 100 GB for multiple local LLM variants Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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.

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