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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Famous Vision Language Models and Their Architectures
| Date | Stars |
|---|---|
| 2026-07-24 | 1284 |
| 2026-07-25 | 1284 |
| 2026-07-28 | 1286 |
| 2026-07-30 | 1286 |
| 2026-07-31 | 1285 |
| 2026-08-06 | 1285 |
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# 👁️🗨️Awesome VLM Architectures [](https://awesome.re) | [DualView](https://dualview.ai)  **Vision-Language Models (VLMs)** feature a multimodal architecture that processes image and text data simultaneously. They can perform **Visual Question Answering (VQA)**, **image captioning** and **Text-To-Image search** kind of tasks. VLMs utilize techniques like multimodal fusing with cross-attention, masked-language modeling, and image-text matching to relate visual semantics to textual representations. This repository contains information on famous Vision Language Models (VLMs), including details about their architectures, training procedures, and the datasets used for training. **Click to expand for further details for every architecture** - 📙 <a href="https://github.com/gokayfem/ComfyUI_VLM_nodes">Visit my other repo to try Vision Language Models on ComfyUI</a> ## Contents - [Architectures](#architectures) - [Important References](#important-references) - [Tools](#tools) ## Models [LLaVA](#llava-large-language-and-vision-assistant---visual-instruction-tuning) | [LLaVA 1.5](#llava-15-improved-baselines-with-visual-instruction-tuning) | [LLaVA 1.6](#llava-16-llava-next-improved-reasoning-ocr-and-world-knowledge) | [PaliGemma](#paligemma-a-versatile-and-transferable-3b-vision-language-model) | [PaliGemma 2](#paligemma-2-a-family-of-versatile-vlms-for-transfer) | [AIMv2](#aimv2-multimodal-autoregressive-pre-training-of-large-vision-encoders) | [Apollo](#apollo-an-exploration-of-video-understanding-in-large-multimodal-models) | [ARIA](#aria-an-open-multimodal-native-mixture-of-experts-model) | [EVE](#eve-unveiling-encoder-free-vision-language-models) | [EVEv2](#evev2-improved-baselines-for-encoder-free-vision-language-models) | [Janus-Pro](#janus-pro-unified-multimodal-understanding-and-generation-with-data-and-model-scaling) | [LLaVA-CoT](#llava-cot-let-vision-language-models-reason-step-by-step) | [LLM2CLIP](#llm2clip-powerful-language-model-unlocks-richer-visual-representation) | [Maya](#maya-an-instruction-finetuned-multilingual-multimodal-model) | [MiniMax-01](#minimax-01-scaling-foundation-models-with-lightning-attention) | [NVLM](#nvlm-open-frontier-class-multimodal-llms) | [OmniVLM](#omnivlm-a-token-compressed-sub-billion-parameter-vision-language-model-for-efficient-on-device-inference) | [Pixtral 12B](#pixtral-12b-a-cutting-edge-open-multimodal-language-model) | [Sa2VA](#sa2va-marrying-sam2-with-llava-for-dense-grounded-understanding-of-images-and-videos) | [Tarsier2](#tarsier2-advancing-large-vision-language-models-from-detailed-video-description-to-comprehensive-video-understanding) | [UI-TARS](#ui-tars-pioneering-automated-gui-interaction-with-native-agents) | [VideoChat-Flash](#videochat-flash-hierarchical-compression-for-long-context-video-modeling) | [VideoLLaMA 3](#videollama-3-frontier-multimodal-foundation-models-for-image-and-video-understanding) | [Llama 3.2-Vision](#llama-32-vision-enhanced-multimodal-capabilities-built-on-llama-3) | [SmolVLM](#smolvlm-a-small-efficient-and-open-source-vision-language-model) | [IDEFICS](#idefics) | [IDEFICS2](#idefics2) | [IDEFICS3-8B](#idefics3-8b-building-and-better-understanding-vision-language-models) | [InternLM-XComposer2](#internlm-xcomposer2-mastering-free-form-text-image-composition-and-comprehension-in-vision-language-large-model) | [InternLM-XComposer2-4KHD](#internlm-xcomposer2-4khd-a-pioneering-large-vision-language-model-handling-resolutions-from-336-pixels-to-4k-hd) | [InternLM-XComposer-2.5](#internlm-xcomposer-25-a-versatile-large-vision-language-model-supporting-long-contextual-input-and-output) | [InternVL 2.5](#internvl-25-expanding-performance-boundaries-of-open-source-multimodal-models-with-model-data-and-test-time-scaling) | [DeepSeek-VL](#deepseek-vl-towards-real-world-vision-language-understanding)
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matched fp:46b5a4f04294b8c7, topic:multimodal, topic:vision-language-model, topic:vlm