Infrastructure & deployment
ModelExpress: Distributing Model Artifacts at the Speed of Light
ModelExpress avoids repeated model-weight cold loads by finding a compatible serving peer first, then transferring weights directly GPU-to-GPU when possible.
Why it matters: For teams scaling model replicas, avoiding repeated storage downloads and host copies can reduce time spent waiting for workers to become useful. MX also targets startup work beyond weight loading, while selecting paths and fallbacks based on available capabilities.