Caverno vs KitLLM

Caverno is a powerful chat client for locally-hosted LLMs. Connect to Ollama, LM Studio, vLLM, or any OpenAI-compatible API endpoint and start chatting — no cloud required. KEY FEATURES • Any OpenAI-Compatible Server Connect to your own LLM running on localhost or your local network. Supports any endpoint that speaks the OpenAI API format. • Tool Calling (MCP Protocol) Extend your AI with real-time tools — web search, calculator, code execution, and more. Caverno uses the Model Context Protocol to let your LLM take actions. • Session Memory Your assistant remembers your preferences, constraints, and context across conversations. Memory is stored locally and fully under your control. • Voice In & Out Speak your messages and have responses read aloud. Configurable speech rate and auto-read options. • Image Attachments Attach photos from your library to include visual context in your conversations. • Multiple Conversations Create, switch, and manage separate chat threads. All conversations are persisted locally. • Assistant Modes Switch between General and Coding modes for different response styles tailored to your task. • Privacy First No account required. No data sent to third parties. All conversations and memory stay on your device — the only network connection is to the server you configure. GETTING STARTED 1. Install an OpenAI-compatible LLM server (Ollama, LM Studio, etc.) 2. Open Caverno and go to Settings 3. Enter your server URL and select a model 4. Start chatting! Caverno is designed for developers, AI enthusiasts, and anyone who wants full control over their AI assistant.

KitLLM turns your phone or tablet into a private AI assistant. Import a GGUF model from your files or browse the public Hugging Face catalog, load it locally, and chat without sending your conversations to the cloud. Key features include GGUF import and validation, compatibility estimation, resumable downloads, fully local conversations, instant generation stop, and device diagnostics. Performance, memory requirements, and response quality depend on both the selected model and your device. Models are provided by their respective authors and may be subject to their own licenses.