Idle Macs Can Also Make Money? An Overview of Eigen Labs' Decentralized AI Inference Network Darkbloom
AI inference is becoming a crucial layer of internet infrastructure, yet it remains largely dependent on costly, capacity-limited centralized systems with potential security risks. Meanwhile, millions of powerful computers sit idle globally. Eigen Labs' Darkbloom network aims to utilize this idle capacity by enabling distributed AI inference on Mac computers, specifically those with Apple Silicon chips.
Darkbloom's architecture consists of three components: users who send inference requests, a coordinator (operated by Eigen Labs) that routes these requests, and providers (Mac owners) whose machines run the models and return outputs without being able to see the request content. The system prioritizes privacy through a hardened provider process, software integrity checks, and hardware-supported attestation based on Apple's security architecture to ensure verifiable privacy.
Economically, Darkbloom differs from traditional models. It leverages existing hardware, with marginal costs primarily driven by electricity, allowing it to offer pricing roughly 50% lower than major API aggregators. Providers keep 100% of the inference revenue, and the project does not rely on token subsidies; earnings come solely from real AI inference demand. However, early-stage earnings are modest, with top providers currently earning under $6 per day, influenced by factors like hardware specs, uptime, and network demand. The network currently supports models like Google's Gemma 4 and OpenAI's GPT-OSS via OpenRouter.
To participate as a provider, users need an Apple Silicon Mac running macOS 14 or later, must install the Darkbloom provider software, and keep the machine online with a stable internet connection.
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