SANYAMWADHWA.TECH :: PROJECT :: GARUDAAI --- SUMMARY ---TITLE............. GarudaAI — Local LLM Setup and Remote Access CLIDATE.............. January 2026CATEGORY.......... SystemsPROBLEM........... Running a local LLM requires knowing your GPU specs, picking quantization levels, and configuring remote access. GarudaAI collapses the entire setup into one command.WHAT IT DOES...... Linux CLI tool that profiles GPU specs, determines which local LLMs can run efficiently on the hardware, installs Ollama with the optimal model, and exposes a remote-access endpoint reachable from any phone on the network. --- RESULT --- --- WHAT I BUILT ---HIGHLIGHT 1....... GPU profiling pipeline that matches VRAM and compute against model quantization requirements to recommend the best-fit local LLM.HIGHLIGHT 2....... One-command setup: installs Ollama, pulls the right model, and tunnels a mobile-accessible endpoint for on-the-go inference. --- HOW IT WORKS ---STEP 1............ Python CLISTEP 2............ GPU Hardware Profiler (VRAM + compute detection)STEP 3............ Ollama Auto-InstallerSTEP 4............ Model PullSTEP 5............ Network Tunnel (mobile remote access) --- FEATURES ---FEATURE 1......... Profiles GPU VRAM and compute against quantization tables (Q4_K_M, Q5, Q8, fp16)FEATURE 2......... Recommends the highest-quality model your hardware can actually runFEATURE 3......... Automatically installs Ollama and pulls the matched model without manual stepsFEATURE 4......... Exposes a mobile-accessible inference endpoint via network tunnelFEATURE 5......... Supports LLaMA 3, Mistral, Phi-3, and all Ollama-compatible model families --- STACK ---STACK............. Python, Ollama, Linux, Shell, LLM --- LINKS ---CODE.............. https://github.com/SanyamWadhwa07/Garuda_AIHUMAN PAGE........ https://sanyamwadhwa.tech/projects/garudaai