LM Pocket App-Analysen für 6. Oktober

Discover, download, and run open-source AI models directly on your device. No cloud. No subscription. No data leaves your device. LM Pocket brings the power of local AI models to your device. Browse thousands of GGUF models on Hugging Face, download them over WiFi, and chat with them entirely on-device. COMPLETELY PRIVATE Every conversation stays on your device. No server, no API key, no account required. Your prompts and responses never leave the device. DISCOVER MODELS Browse Hugging Face Hub for quantized GGUF models. Filter by size, quantization level, and popularity. See compatibility badges that tell you which models will run well on your device before downloading. CHAT WITH AI Stream token-by-token responses with full Markdown rendering. Manage multiple conversations. Adjust temperature, top-p, top-k, context length, and more. Supports ChatML, Llama, Mistral, Phi, Gemma, and other prompt formats automatically. LOCAL API SERVER Run an OpenAI-compatible HTTP server on your device. Expose /v1/chat/completions, /v1/models, and /v1/embeddings endpoints on your local network. Connect any app that supports the OpenAI API format. MANAGE YOUR LIBRARY Track installed models with storage usage. Import GGUF files from the Files app. Load and unload models with one tap. Monitor real-time performance: tokens per second, memory usage, and thermal state. BUILT FOR POWER USERS - GPU acceleration for fast inference - Background downloads with pause and resume - Hardware-aware model recommendations - Chat template auto-detection - Conversation export as JSON or Markdown - JSON mode with grammar-constrained output - Embeddings generation 100% FREE No subscriptions, no in-app purchases, no ads. Open-source AI should be accessible to everyone. SUPPORTED MODELS Run any GGUF-quantized model: Llama, Mistral, Phi, Gemma, CodeLlama, DeepSeek, Qwen, and thousands more from Hugging Face Hub. Model performance depends on device RAM and model size. Terms of Service: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/