Molmo 2 | A new standard for open video intelligence

2025-12-16 · Source: Ai2 · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

Molmo 2, the next generation of the open-source multimodal AI, extends its intelligence from image understanding to video analysis. This new version can count and track objects or actions within videos, answer complex questions about video content, and generate step-by-step instructions from cooking videos. Molmo 2 is trained on the largest fully open video-centric multimodal corpus available, integrating an LLM's fluid intelligence with an image encoder's spatial awareness. It also features artifact detection to identify anomalies in potentially artificially generated videos and can reason across multiple simultaneous inputs, including images, documents, and live video streams. Molmo 2 is now openly available for researchers and builders.

Key takeaway

For AI Scientists and Machine Learning Engineers working with video data, Molmo 2 offers a robust, open-source foundation for advanced video understanding. You should explore its capabilities for tasks like object tracking, complex query answering, and anomaly detection, potentially integrating it into your research or application development workflows to leverage its multimodal reasoning across diverse input streams.

Key insights

Molmo 2 provides open-source multimodal video intelligence, combining LLM reasoning with spatial awareness for diverse video analysis tasks.

Principles

• Multimodal intelligence extends to video.
• Open-source models foster research and customization.

Method

Molmo 2 integrates an LLM's fluid intelligence with an image encoder's spatial awareness, trained on a large, open video-centric multimodal corpus.

In practice

• Track objects/actions in video.
• Generate instructions from video.
• Detect video artifacts.

Topics

• Video Intelligence
• Multimodal AI
• Object Tracking
• Large Language Models
• Open-Source AI

Best for: Machine Learning Engineer, Computer Vision Engineer, AI Scientist, AI Researcher, AI Engineer, Software Engineer

Related on AIssential

• Getting Started with Molmo2 — Molmo2 is a multimodal model for image VQA, video VQA, and image pointing.
• Molmo 2 | Video Tracking — Momo 2's video tracking combines strong perception and reasoning for robust object re-identification across occlusions and disappearances.
• Watch, Remember, Reason: Human-View Video Understanding with MLLMs — MLLM video understanding benefits from a human-like "watch, remember, reason" functional decomposition.
• Molmo 2 | Complex video question answering — Molmo 2 demonstrates advanced open-source video Q&A capabilities through detailed, instruction-following responses, enabled by new open-source training data.
• MAVEN: A Multi-stage Agentic Annotation Pipeline for Video Reasoning Tasks — MAVEN's agentic, multi-stage pipeline automates high-quality, domain-adaptable video annotation for VLM training.
• 🤖 MolmoAct 2: An open foundation for robots that work in the real world — MolmoAct 2 offers an open foundation for real-world robot learning with enhanced perception and action models.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Ai2.