LobeChat vs SillyTavern

LobeChat, presented by LobeHub as an agent collaboration platform, brings together persistent agent memory, multi-agent workflows and model orchestration for work and productivity. Agent Groups can form teams automatically, collaborate in parallel, handle multiple tasks and improve results iteratively. Workflow components include Pages, scheduled tasks, Projects and shared Workspaces. Agents can use personal and structured editable memory, with continual learning and adaptive behavior. The platform describes coordination across models and modalities, and its Agent Marketplace offers customizable agents for writing, Q&A, images, video, voice and workflows. Agents can connect to tools and APIs through MCP; listed Skills are compatible with Claude Code, Codex CLI and ChatGPT. LobeChat is available on web, Android, iOS, Linux, macOS, Windows and through self-hosting. Its desktop downloads cover Apple Silicon and Intel Macs, and the desktop app is described as running locally. Cloud plans meter model use in credits and set file and vector storage limits. A Free plan is available; paid plans start at $12.90/mo, with a free trial listed.

SillyTavern is a locally installed interface for interacting with text-generation models, image-generation engines, and text-to-speech voice models. Users can create, import, and switch between character cards, then return to chat histories or review them. The interface includes group chats, lorebooks, personas, prompt controls, chat commands, scripting, and built-in retrieval-augmented generation. Extensions can add character sprites, chat summarization and translation, image generation, text-to-speech, and web search. SillyTavern works with local and cloud model backends, including KoboldCpp, llama.cpp, Ollama, OpenAI, Claude, Mistral, OpenRouter, and AI Horde. The project says it will remain free and open source under AGPL-3.0 and provides no hosted service. It says it does not programmatically track user data, though cloud providers may log information sent to them. Local use requires a system supporting NodeJS 20 or higher; documentation recommends an NVIDIA 3000-series GPU with at least 6GB of VRAM for local inference. The app was not designed for very large character libraries, and performance can degrade above 1,000 characters.