Inference Acceleration

Accelerate model distribution for vLLM, SGLang, and more.

Zero-Wait Distribution

Eliminate bandwidth bottlenecks with a "Pull-once, serve-all" cache, enabling 10Gbps+ speeds across 100+ GPU nodes simultaneously. MatrixHub completely changes the startup performance of large inference clusters.

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Pull-Once, Serve-All

The first request fetches the model from the public source and persists it locally. Subsequent nodes read from MatrixHub over the local network instead of re-downloading.

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P2P Distribution

Future native support for P2P distribution to handle startup storms when hundreds of inference nodes initialize simultaneously.

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NetLoader

Designed for direct-to-GPU weight streaming, bypassing disk I/O bottlenecks for ultimate acceleration.