Base Compute
BaseRT runs AI language models directly on your Mac's own chip instead of a data center — once it's running, there's no per-message bill because there's no server in the loop at all.
🔗 Visit Base Compute
Description
Every message sent to a cloud AI model costs money and depends on an internet connection and someone else's server staying up. BaseRT takes the opposite approach: a runtime specifically tuned for Apple Silicon that runs the model's computation directly on your own hardware, so once it's set up there's no per-token fee and no network dependency for inference.
BaseRT is open source (Rust-based, github.com/basecompute/baseRT, 110 stars) and focuses specifically on hardware- and model-level optimization for fast, private, low-latency local execution — the pitch is genuinely near-zero marginal cost after the initial setup, since you're using compute you already own. The team, based in Melbourne and Berlin, launched the project in June 2026 with an explicit long-term mission of making increasingly capable AI models runnable on ordinary consumer devices rather than requiring cloud infrastructure.
💬 Our review
The short version: BaseRT is for developers running local AI on Apple Silicon who want speed and privacy without an ongoing API bill — not for anyone who needs the largest, most capable frontier models, which still require far more compute than a laptop or desktop chip provides.
Optimizing specifically for Apple Silicon rather than trying to be hardware-agnostic is a smart, focused bet — general-purpose local inference tools often leave real performance on the table because they don't exploit chip-specific capabilities, and a narrower focus usually means better results on that specific hardware. Being open source with real GitHub activity (110 stars, active repo) gives some confidence this isn't vaporware. The honest limitation is capability ceiling: local, on-device models are meaningfully smaller and less capable than the frontier cloud models from major labs, so this is a good fit for privacy-sensitive or cost-sensitive workloads that don't need cutting-edge reasoning, not a full cloud-API replacement.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Gratuit et open source ; coût marginal quasi nul une fois déployé sur votre propre matériel ; Enterprise sur devis
Pros
Optimisé spécifiquement pour Apple Silicon
Coût marginal quasi nul après déploiement
Open source avec activité GitHub réelle
Confidentialité totale, aucune dépendance réseau
Cons
Modèles locaux moins capables que les modèles cloud de pointe
Réservé au matériel Apple Silicon
Projet encore jeune (juin 2026)