The Best GUIs for Running Your Own Local AI in 2025

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Why? Because someone asked…

If you’re looking to run your own private AI assistant at home—without relying on the cloud or subscriptions—you’ll need a solid GUI to manage and interact with local models like LLaMA or Mistral. Whether you’re after simplicity, deep customization, or roleplay features, there are several great open-source interfaces to choose from. Here’s a quick rundown of the best GUIs for running your own AI locally in 2025.

Here are the top options in 2025 based on usability, features, and community support:


🏆 Top GUIs for Running Your Own Local AI

1. OpenWebUI (You already mentioned)

  • 🟢 Best for: Clean, modern UI and multi-user support
  • ✅ Chat history, prompt templates, multi-model
  • 🔌 Works great with Ollama, LM Studio, GPTQ, etc.
  • 🌐 Web-based, cross-platform

GitHub: open-webui/open-webui


2. Text Generation WebUI (oobabooga)

  • 🟢 Best for: Custom model tweaking, dev tools, advanced control
  • ✅ Extensive support for quantized models (GGUF, GPTQ, etc.)
  • 🧩 Extensions: LoRA, memory, APIs, character roleplay
  • 🧠 Ideal for power users and developers

GitHub: oobabooga/text-generation-webui


3. LM Studio

  • 🟢 Best for: Windows/Mac users wanting a simple GUI for local models
  • ✅ Plug-and-play LLaMA/Mistral, integrated Ollama support
  • ❌ Limited customizability compared to OpenWebUI or oobabooga

Website: lmstudio.ai


4. KoboldCPP / KoboldAI

  • 🟢 Best for: Roleplay, storytelling, and fan-fiction AI use
  • 🎭 Great memory features, character context
  • ❌ Less suited for general-purpose assistant tasks

GitHub: LostRuins/koboldcpp


5. Jan / JanAI

  • 🟢 Best for: Clean OpenAI-style experience with local models
  • ✅ Supports chat history, multi-model use
  • 🧪 Still early stage, but promising

GitHub: jan-ai/jan


🛠️ Bonus: Infrastructure

If you’re building your own AI stack, these tools can help:

  • Ollama – Easiest way to run models like LLaMA, Mistral
  • LMDeploy or vLLM – For production-grade inference
  • LangChain/LLM Studio – For agents/tools integration

🧠 Best Combo (2025 Recommendation)

If you’re serious about running your own AI:

  • Use Ollama to manage models
  • Pair with OpenWebUI (for chat) or Text Generation WebUI (for control)
  • Use LM Studio for casual desktop use

Here’s everything you need to get started with Ollama and OpenWebUI, including official links and installation instructions.


🐪 Ollama – Run LLaMA, Mistral, and more locally

🔗 Official site:

👉 https://ollama.com

📦 Install Ollama on Ubuntu / Linux:

curl -fsSL https://ollama.com/install.sh | sh

Then run a model (example: Mistral):

ollama run mistral

Or list available models:

ollama list

🌐 OpenWebUI – Web-based chat interface for local models

🔗 GitHub:

👉 https://github.com/open-webui/open-webui

📦 Install with Docker (recommended):

docker run -d \
  -p 3000:3000 \
  -v openwebui:/app/backend/data \
  -e 'OLLAMA_BASE_URL=http://host.docker.internal:11434' \
  --name openwebui \
  ghcr.io/open-webui/open-webui:main

⚠️ Make sure Ollama is running first, and port 11434 is accessible.


🧠 How They Work Together

  1. Ollama runs your models (like LLaMA or Mistral) locally.
  2. OpenWebUI connects to Ollama and provides a nice web-based chat interface.
  3. You can access it at:
    🔗 http://localhost:3000

 

 

 


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