SmolLM 3 3B
HuggingFace's small-model line at 3B. Apache 2.0. Designed for edge / educational deployments.
Overview
HuggingFace's small-model line at 3B. Apache 2.0. Designed for edge / educational deployments.
Strengths
- Apache 2.0
- Strong reasoning per parameter at 3B
Weaknesses
- 3B ceiling
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 1.8 GB | 3 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of SmolLM 3 3B.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run SmolLM 3 3B?
Can I use SmolLM 3 3B commercially?
What's the context length of SmolLM 3 3B?
Source: huggingface.co/HuggingFaceTB/SmolLM3-3B
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify SmolLM 3 3B runs on your specific hardware before committing money.