RAG/edge: Gemma4 GGUF/INT4 phones/Mac/Pixel/M4/eGPU, Qwen low-VRAM/LoRA/SAM3, Llama4 chunking, CIQ FuzzBall, Gemini MediaTek/Home/Copilot/Weaviate
Key Questions
What enables Gemma4 on edge devices?
Gemma4 GGUF/INT4 runs offline on phones (Pixel), Mac (M4), eGPU, Jetson. Supports Edge Gallery agentic trends, Claude hybrids. Apple now supports M-series eGPUs officially.
How does Qwen run on low-VRAM setups?
Qwen3.6 Ollama uses low-VRAM, LoRA, SAM3 for finance. Local apps like PocketPal integrate Qwen/Llama. Runs 70B models on 4GB GPU.
What chunking strategies for Llama4?
Llama4 handles 10M chunking for local RAG. Pros use advanced techniques for efficiency. Supports OpenRouter API with local models.
What is CIQ FuzzBall?
CIQ's FuzzBall advances edge RAG. Part of ongoing quants/latency optimizations. Complements Qdrant $50M vector DB.
How does Gemini Nano work on devices?
Gemini Nano/MediaTek for Home, low-resource local apps. Runs on phones without internet via 5 free apps. Copilot faces RAM bloat issues.
What Apple hardware supports local AI?
Apple eGPU for M-series Macs, TinyCorp integration. Approved AMD/Nvidia drivers for AI, not gaming. Enables Gemma4 on MacBook Pro M4 via Ollama/llama.cpp.
What local LLM efficiency tips?
Lean models run without GPU; George Hotz plans $100 AI box. Gemma4 benchmarks on Jetson Orin Nano vs RTX/DGX. Hailo edge AI chips go public via SPAC.
What is LLM Wiki RAG focus?
LLM Wiki covers RAG trends, Karpathy insights. Ongoing evals for quants/latency/TCO. Local agents like Claude Code with Gemma/Qwen hybrids.
Gemma4 GGUF/INT4 offline (Pixel/M4/Jetson); Qwen3.6 Ollama low-VRAM/LoRA/SAM3; Llama4 10M chunking; Gemini Nano/MediaTek/Home; CIQ FuzzBall; Qdrant $50M; Copilot RAM; LLM Wiki RAG; Weaviate PDF Agent Skills; Apple eGPU. Ongoing quants/latency/TCO/evals.