LLaVA (Large Language and Vision Assistant) brings multimodal AI — the ability to understand and discuss images — to your local machine via Ollama. It opens up a whole new class of AI workflows beyond text.
Askimo App gives LLaVA a complete desktop workspace: persistent chat history, local file search (RAG), multi-step AI Plans, MCP tool integrations, and the ability to combine vision tasks with cloud providers, all in one native app.
LLaVA is an open-source multimodal large language model that combines a vision encoder with a language model backbone to understand and reason about images. Originally developed by researchers at the University of Wisconsin-Madison and Microsoft Research, LLaVA is freely available and runs locally through Ollama, bringing vision AI capabilities to consumer hardware.
Developer
University of Wisconsin-Madison / Microsoft Research
License
Apache 2.0
Best For
Multimodal image understanding
Askimo is not a thin wrapper. It's a full local AI workspace that lets you combine LLaVA's vision capabilities with RAG, workflows, and multi-provider switching.
Built as a true desktop app for macOS, Windows, and Linux. Fast, responsive, and works fully offline with no browser or server required.
Seamless model selection, endpoint configuration, and switching. See the Ollama provider setup guide for full details.
Index your project files, PDFs, and documents with Apache Lucene + jvector. The model answers questions grounded in your own knowledge base.
Use the visual interface for daily work and the Askimo CLI for scripting and automation. Same provider config, seamless switching.
Chain multiple prompts into automated workflows (research, summarise, write) all in one click. No copy-pasting between windows.
All conversations and files stay on your device. No telemetry, no cloud sync, no data collection. Learn more about Askimo security.
Running LLaVA through Askimo takes under 5 minutes.
Run ollama pull llava in your terminal.
Launch Askimo App and choose Ollama as your provider. Set the endpoint to http://localhost:11434.
Select LLaVA from the model list and start using vision AI locally. Combine with RAG to index documents and get grounded, image-aware answers.
CLI example:
askimo --provider ollama --model llava -p "What is in this image?" A fair feature comparison of the three most common ways to run LLaVA locally in 2026.
| Feature | Askimo App | Ollama CLI | Open WebUI |
|---|---|---|---|
| Visual chat interface | |||
| RAG (chat with your own files) | |||
| Multi-provider support (Ollama + cloud) | |||
| Conversation history and search | |||
| Open source (OSI-approved license) | |||
| Run models fully locally (100% private) | |||
| Native desktop app (no server or browser) | |||
| Works fully offline (no server process) | |||
| CLI interface for scripting | |||
| Local code block execution (Python, Bash) | |||
| MCP tools (file, git, web, APIs) | Partial | ||
| AI Plans (chained multi-step prompts) | |||
| Server-side pipelines / automation | Team edition (coming soon) | ||
| Multi-user / team features | Team edition (coming soon) | ||
| Web browser access (no app install) |
checkmark = included · x = not available · text = partial support. Based on publicly documented features as of 2026. Open WebUI uses a proprietary license (not OSI open source). Ollama CLI is open source (MIT).
Real workflows that benefit from running multimodal AI locally.
Analyse screenshots, product photos, diagrams, and scanned documents without sending anything to a cloud vision API. Everything stays on your machine.
Combine LLaVA with Askimo RAG to ask questions about image-heavy PDFs, technical diagrams, and visual reports, fully offline.
Use AI Plans to chain vision analysis with text generation. Describe an image, summarise findings, then draft a report — all automated in one plan.
Common questions about running LLaVA locally with a desktop GUI.
Askimo App is the most full-featured desktop client for LLaVA in 2026. It provides a native app for macOS, Windows, and Linux with local RAG, MCP tools, AI Plans, persistent chat history, and multi-provider switching — all while keeping your images and data completely offline.
LLaVA can describe images, answer questions about photos and screenshots, analyse diagrams, read text in images (OCR-style), identify objects and scenes, and reason about visual content in natural language.
LLaVA running locally via Ollama is slightly less capable than the latest GPT-4 Vision or Gemini Vision, but it's free, fully private, and runs offline. For most document and image analysis tasks, it's more than sufficient.
Yes, LLaVA can read and transcribe text visible in images with reasonable accuracy. For heavy OCR workloads, a dedicated OCR tool may be better, but for reading labels, captchas, screenshots, and document scans, LLaVA works well.
Yes. LLaVA runs entirely on your machine via Ollama. Your photos are never uploaded anywhere. Askimo adds no cloud sync or telemetry, so your images stay completely private.
Step-by-step instructions for connecting Ollama to Askimo App.
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Free • Open Source • Privacy-First • Works Offline