The fastest way to get this model running locally is via Optional Features.

Please follow the instructions listed below to get started.

Everything happens automatically, including the heavy cloud asset download.

The installer diagnoses your environment to deploy the most compatible profile.

📘 Build Hash: 57ea0a1c3d8bb5c8cc49d64205068af2 • 🗓 2026-07-02 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed to prevent memory swapping to disk Disk Space: free: 80 GB on system drive for scratch space GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

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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