Moondream 2
Tiny vision-language model. ~1.9B; designed for edge / embedded multimodal use cases. Apache 2.0.
Overview
Tiny vision-language model. ~1.9B; designed for edge / embedded multimodal use cases. Apache 2.0.
Strengths
- Apache 2.0 multimodal at 1.9B
- Edge-deployable
Weaknesses
- Quality ceiling at 1.9B parameters
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_0 | 1.7 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 Moondream 2.
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 Moondream 2?
Can I use Moondream 2 commercially?
What's the context length of Moondream 2?
Does Moondream 2 support images?
Source: huggingface.co/vikhyatk/moondream2
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Moondream 2 runs on your specific hardware before committing money.