mLiveViewLite vs mycellm

mLiveView is the innovative software for viewing the video of plug n play IP Cameras on iPhone/iPod touch/iPad. No public IP address is needed for the IP camera, no port mapping or DDNS is needed for router configuration. It is simply enough to just key in the ID/password of the IP camera to see the video from your iPhone/iPod touch anywhere, anytime. Besides the live video viewing, remote video settings update, on-screen pan/tilt control, audio, finger-zooming and snapshot are also supported.

Mycellm turns your iPhone or iPad into a node on a distributed AI inference network. Run open LLMs on your own hardware — no account, no telemetry, no cloud middleman. Use it three ways, and own every layer. LOCAL — ON YOUR DEVICE Load a model and run inference entirely on-device. Fully offline, airplane-mode friendly. On-device Privacy Guard scans prompts for secrets before anything hits the wire. TRUSTED DEVICES — YOUR OWN NETWORK Point your phone at a node you trust — your Mac Studio, your iPad Pro, your homelab — and run models far bigger than any single device could hold. Your phone stays light; a machine you own does the heavy lifting. No cloud. PUBLIC — THE FREE NETWORK Tap the public mycellm net: open models served by GPUs worldwide. Earn credits by serving spare compute, spend them to run larger models. Peer-to-peer, no subscription. FEDERATE Stand up your own network with its own trust policy and credit ledger, mint invite tokens, and bridge trusted networks with cross-network routing. You decide membership, models, and data flow. UNLEASH THE iPAD PRO An iPad Pro (M4/M5) is a serious AI machine that sits idle most of the day. Put it to work: more unified memory runs larger models, Metal delivers 30+ tok/s on multi-billion-parameter models. Serve your iPhone, your team, or the network — first-class on any device that runs a model. FOR PEOPLE WHO RUN THEIR OWN STACK - Serves the same chat-completions REST API your tools already speak — point curl, Claude Code, or your own clients at your device. - Vision models: attach an image and ask, on-device. - Live dashboard: tok/s, credits, peers, node health. - Auto hardware-fit: picks quantizations that match your RAM. - Open source, Apache 2.0. Audit it, fork it, run it. No black boxes, no lock-in. It's BitTorrent for LLMs — every node both uses the network and makes it stronger. Full docs and use cases at mycellm.dev. Bring your own models, keep your data, and run AI on your terms.