Vision Language Models (Better, faster, stronger) — new models and techniques

AI Impact Summary

Recent advancements in Vision Language Models (VLMs) are characterized by a shift towards smaller, more powerful models, driven by techniques like Mixture-of-Experts (MoE) decoders and model distillation. Key developments include models like Qwen 2.5 Omni, MiniCPM-o 2.6, Janus-Pro-7B, and SmolVLM, demonstrating capabilities in reasoning, multimodal understanding, and even agentic behavior across various modalities (image, text, audio, video). These models are increasingly accessible on consumer GPUs, opening up new possibilities for local execution and data privacy.