GoKawiilDevelopers release open-source Edge0-145B on-device AI model
A development team has open-sourced Edge0-145B and Edge0-120B, two on-device AI models, alongside an inference framework and deployment tools. Edge0-145B is described as the first open-source on-device model with 145 billion parameters, running locally on a compatible laptop with reported peak memory of 29GB and decoding speeds above 80 tokens per second.
GoKawiil's interpretation of the reporting above, not reported fact.
By running a 145-billion-parameter model locally, the release could let developers avoid recurring cloud API fees and keep sensitive data on-device, since core capabilities reportedly work offline. The claim that the model's coding and reasoning performance rivals frontier cloud models comes from the team itself, so independent verification would clarify how it actually compares in practice.
- Edge0-145B is billed as the first open-source 145B-parameter on-device AI model.
- It reportedly runs on a laptop with 29GB peak memory and over 80 tokens/s decoding speed.
- Full model weights, framework, and app are released for developers to reproduce, fine-tune, or integrate.
Apple MacBook Pro 16-inch M3 Max — Running a 145B-parameter model locally demands serious unified memory and bandwidth, which is exactly what the M3 Max chip delivers. Its high-memory configurations make it one of the few consumer laptops actually capable of handling edge AI models like Edge0-145B without choking on memory limits. It's a great match for anyone wanting to experiment with frontier-level on-device AI right now.
See Apple MacBook Pro 16-inch M3 Max on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: edge0.ai, 2026-11-12
Published there as: “Edge0-145B: Frontier AI Capabilities on Your Own Computer”
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