Molmo
VerifiedAi2's fully open multimodal models for image and video understanding
Product preview
Molmo
What it is
Molmo is a family of open vision language models from Ai2, the Allen Institute for AI. The models answer questions about images, sets of images and videos, write detailed captions, and can point to or count objects, which is useful for grounding answers in what is actually on screen. Molmo 2 extends this to video tracking and long video question answering, with 4B and 8B variants and a 7B version built entirely on Ai2's open Olmo language model. Ai2 releases weights, code, evaluation tools and many of the training datasets, so researchers can inspect and adapt every part. Anyone can try the models for free in Ai2's online playground.
Key features
- Image and video question answering
- Object pointing, counting and tracking
- Open weights, code and datasets
- Free online playground
What we liked
- + Fully open, including training data
- + Strong grounding with pointing
- + Compact sizes for workstations
Worth noting
- · Research focus, not a polished consumer app
- · Self-hosting needs GPU resources
Editor's notes
More context from AI BirdView
Molmo stands out for how much Ai2 shares. Many open-weight models release only the final weights, but Ai2 also publishes training datasets, code and recipes, and one Molmo 2 variant uses a fully open language backbone so every component can be examined. Its pointing ability, where the model marks the exact spot it is talking about, makes answers easier to check.
- Molmo 2 handles single images, multiple images and video, including tracking objects across frames.
- Pointing and counting let the model show where things are instead of only describing them.
- The 4B and 8B models are sized to run on a strong workstation for research and prototyping.
- Ai2 released new open datasets for dense video captions, long-form video questions and tracking.
- A free playground lets anyone try the models in a browser without setup.
Molmo is best for researchers, students and developers building vision features who value transparency and want to fine tune or audit their models. A practical tip: start in the Ai2 playground with your own images or short clips to see how pointing performs on your use case, then download the matching variant from the Molmo page when you are ready to run it locally.
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