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Deltafin runs 2.8T Kimi K3 MoE on Apple Silicon

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Deltafin runs 2.8T Kimi K3 MoE on Apple Silicon
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// 1h agoOPENSOURCE RELEASE

Deltafin runs 2.8T Kimi K3 MoE on Apple Silicon

Deltafin is an open-source project by Gavamedia that allows users to execute Kimi K3, a massive 2.8-trillion-parameter Mixture-of-Experts (MoE) model, on consumer Apple Silicon hardware. By dynamically streaming required expert weights over HTTP into a local disk cache with Metal optimizations, it achieves local inference and provides an OpenAI-compatible API endpoint.

// ANALYSIS

Dynamic expert streaming for MoE models is a game-changer that proves clever software engineering can bypass strict hardware VRAM limits for local AI.

* Enables local execution of 2.8T parameter models on consumer Apple Silicon hardware.

* Bypasses memory constraints by streaming only necessary MoE expert weights into a local cache.

* Leverages custom MPS and Metal kernels to achieve ~16 seconds per token generation on an M1 Max.

* Includes an OpenAI-compatible API server for immediate UI and agent compatibility.

// TAGS
deltafinaillmlocal-aiapple-siliconm1-maxmoekimi-k3open-sourceinference

DISCOVERED

1h ago

2026-07-29

PUBLISHED

4h ago

2026-07-28

RELEVANCE

8/ 10

AUTHOR

tito