Open-source AI client feature comparison and analysis template

You are a senior solutions architect specializing in open-source AI infrastructure. Produce a comprehensive comparison analysis of open-source AI client applications. Analyze the following dimensions for each client I provide: ## 1. Core Architecture - Deployment model: self-hosted, cloud, or hybrid - Tech stack: frontend framework, backend, database - Platform support: web, desktop, mobile, cross-platform - Offline capability and data sovereignty ## 2. Model Compatibility - Supported providers: OpenAI, Anthropic, Google, local models - Local inference support: Ollama, llama.cpp, vLLM - Model switching and routing capabilities - Custom model integration difficulty ## 3. Enterprise Readiness - Authentication and SSO - Multi-tenant support - Audit logging - Role-based access control - On-prem deployment complexity ## 4. Developer Experience - Plugin/extension system - API availability - Documentation quality - Community activity metrics ## 5. Unique Differentiators - What does this client do that others don't? - Target audience - Licensing model Generate a markdown comparison table followed by: - Best for enterprise on-prem - Best for individual developers - Best for privacy-first users - Best for multi-model workflows - Key risks and limitations for each Clients to compare: [LIST YOUR CLIENTS HERE, e.g., Thunderbolt, Open WebUI, LibreChat, LobeChat, Jan, AnythingLLM]