LLaVA-LLMs designed to connect a vision encoder with a language model logo
AI Tool Profile

LLaVA-LLMs designed to connect a vision encoder with a language model

Large Language and Vision Assistant

Pricing model
Open Source
Price start
Free

Description of LLaVA-LLMs designed to connect a vision encoder with a language model

LLaVA is a large multimodal model designed to connect a vision encoder with a language model for various tasks involving both text and images. You can access LLaVA and try out demos on their official website at llava.hliu.cc. Additionally, you can find the source code for LLaVA on GitHub at github.com/haotian-liu/LLaVA . Overall, LLaVA appears to be a versatile tool for language and vision tasks, with active development and a community of users and developers. It combines vision and language processing capabilities and is being utilized for various applications, including image understanding and analysis. LLaVA (Large Language and Vision Assistant) is an open-source, large multimodal model adept at integrating vision and language understanding. It sets a new benchmark in accuracy for ScienceQA tasks, demonstrating impressive capabilities similar to vision multimodal GPT-4.
llava.hliu.cc
llava.hliu.cc

Key facts

Official site unreachable since 2026-09-24
Pricing model Open source
Free tier Not verified
Starting price Not verified
Data residency Not verified
Compliance (as stated by vendor) Not verified
Integrations Not verified
Public API Not verified
Self-hostable Not verified
Official site Unreachable (auto-checked 2026-09-24)
Last verified not yet

Alternatives & Similar Tools

LongLLaMA-handle very long text contexts, up to 256,000 tokens logo

LongLLaMA is a large language model designed to handle very long text contexts, up to 256,000 tokens. It's based on OpenLLaMA and uses a technique called Focused Transformer (FoT) for training. The repository provides a smaller 3B version of LongLLaMA for free use. It can also be used as a replacement for LLaMA models with shorter contexts.

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Update history

  1. 2026-09-24 · site status updated (auto-check)

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