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image text to text by vikhyatk

moondream2

Moondream2 is a 1.9B parameter vision-language model designed to be the smallest model that can meaningfully answer questions about images. It pairs a SigLIP vision encoder with a Phi-1.5 language backbone and achieves surprising capability at its size.

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From the model card

Fields below are copied from the tags and counters on the HuggingFace repository vikhyatk/moondream2 at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.

Publisher (HF namespace)
vikhyatk
Pipeline tag
image-text-to-text
Library
Transformers
Weight formats
safetensors
License tag
apache-2.0 — read the license file in the repo before relying on it
Downloads (HF counter at last fetch)
1,605,038
Likes (HF counter at last fetch)
1,435
Model card
https://huggingface.co/vikhyatk/moondream2

Use cases

  • On-device image description on phones or edge devices
  • Lightweight visual QA where 7B+ VLMs are too expensive
  • Automated image alt-text generation at scale
  • First-pass image understanding before routing to a larger model

Pros

  • Under 4GB memory footprint — runs on consumer laptops
  • Apache-2.0 licensed
  • Strong benchmark performance per parameter count
  • Active development with frequent checkpoint releases

Cons

  • 1.9B scale misses nuanced visual details that larger models catch
  • Hallucination rate is higher than 7B VLMs on knowledge-grounded visual questions
  • Single image input — no multi-image or video context
  • Limited fine-tuning documentation compared to larger model families

Tags

transformerssafetensorsmoondream1text-generationimage-text-to-textcustom_codedoi:10.57967/hf/6762license:apache-2.0eval-resultsendpoints_compatibleregion:us