Private Inference Network on Idle Macs
Darkbloom Explained
A plain language guide to Darkbloom a private AI inference network that utilizes idle Apple Silicon Mac computing power.
Darkbloom — Cost-Efficient Private AI Inference on Verified Macs
Encrypted inference on hardware-verified Apple Silicon. Comparable model performance, operator-blind privacy, and about 50% lower cost.
Darkbloom — Cost-Efficient Private AI Inference on Verified Macs
Encrypted inference on hardware-verified Apple Silicon. Comparable model performance, operator-blind privacy, and about 50% lower cost.
Darkbloom — Cost-Efficient Private AI Inference on Verified Macs
Encrypted inference on hardware-verified Apple Silicon. Comparable model performance, operator-blind privacy, and about 50% lower cost.
EXO — Run frontier AI locally.
EXO connects your Macs and workstations into one local inference cluster. Run frontier AI locally.
Gajesh on Twitter / X
TL;DRapple has turn on this switch for everyone to participate in decentralized inferenceppl can rent out their unused compute space and anyone can use this with privacy guarantees https://t.co/LTP4zyjsdt pic.twitter.com/8Dvo7XK8jJ— Gajesh (@gajesh) February 18, 2026
Mount Thor — AI Execution Environments on Apple Hardware
Managed macOS environments for AI workloads that require native desktop access, persistent state, or model inference on Apple silicon.
Argmax - Foundation Models On Device
Run private, real-time, and predictable inference workloads directly on users' devices.
Introducing Hybrid Compute on Mac
Perplexity Computer uses cloud AI and local models on Mac, keeping sensitive files and information on the device.
Home - NobodyWho
NobodyWho is an inference engine that lets you run LLMs locally on any device
jundot/omlx
LLM inference server with continuous batching & SSD caching for Apple Silicon — managed from the macOS menu bar
Private Post-Training and Inference for Frontier Models
A technical deep dive of Silo, our local-like privacy stack for cloud-based training and inference of trillion-parameter models.
Apple Private Cloud Compute
Announced at [[Private Cloud Compute New Frontier]] blog post.[[Matthew Green]] initial reaction thread [[Matthew Green Apple PCC Thread]]
Confidential Inference via Trusted Virtual Machines
Announcing a new collaborative research paper on Confidential Inference, a set of tools to improve the security of our model weights and of our users' data
Security research on Private Cloud Compute - Apple Security Research
Private Cloud Compute (PCC) fulfills computationally intensive requests for Apple Intelligence while providing groundbreaking privacy and security protections — by bringing our industry-leading device security model into the cloud. To build public trust in our system, we’re making it possible for researchers to inspect and verify PCC’s security and privacy guarantees by releasing tools and resources including a comprehensive PCC Security Guide, the software binaries and source code of key PCC components, and — in a first for any Apple platform — a Virtual Research Environment, which allows anyone to install and test the PCC software on a Mac with Apple silicon.
