LLaVA

LLaVA is an open multimodal model (“Large Language and Vision Assistant”) that combines a powerful language module (Vicuna, Mistral, Nous Hermes, etc.) with a vision encoder (usually CLIP) and is trained on multimodal instructions. It can process images, diagrams, screenshots, and documents as part of the context and respond in dialogue format: describing an image, extracting text (OCR), analyzing tables and charts, explaining interface content, solving visual tasks, and combining this with regular text queries. New versions such as LLaVA 1.5/1.6 and LLaVA-NeXT strengthen visual reasoning, world knowledge, and performance on high-resolution images. Technically, LLaVA is an auto-regressive Transformer model with a frozen vision encoder and a small projector attached to translate visual features into the token space. Modern builds (for example, LLaVA 1.6 Mistral 7B, LLaVA v1.6-34B, and OneVision 1.5 with 4–34B parameters) support dynamically high resolution up to 672×672 and elongated 336×1344 formats, an improved mix of visual-text data, and long context, making them competitive among open multimodal LMMs. LLaVA can be used to develop “chat with image” experiences for websites and applications, intelligent assistants for working with documents, presentations, and scans, catalog visual search systems, assistants for e-commerce (product photo analysis), UX and analytical tools, educational services, and internal corporate dashboards. The FreeBlock team will select the optimal LLaVA build, fine-tune it on your data (documents, interfaces, catalogs), build a RAG+vision architecture, and integrate the multimodal assistant into your products and business processes. If you want AI to understand not only text but also images, order AI project development based on LLaVA from FreeBlock.