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Universal deployment stack compiling models to Vulkan, Metal, CUDA, and WebGPU via TVM/Unity for phones, browsers, and servers.

Google’s smaller open **weights** Gemma line (Gemma 2/3, etc.) with Gemma license terms, plus `gemma.cpp` for lightweight CPU inference.

Small language model family (Phi-3/4 lineage) emphasizing strong quality per parameter; weights on Hugging Face under Microsoft licenses per release.

1.1B-parameter Llama-architecture model trained on ~3T tokens—Apache-2.0 weights for fast experiments and teaching.

Hugging Face TB small LM family (135M–1.7B) with Apache-2.0 weights aimed at on-device and edge quality per size.

Intel toolkit to optimize and deploy deep learning on Intel CPUs, GPUs, and NPUs with model conversion and runtime APIs.

Google’s cross-platform pipelines for perception: face/hand pose, segmentation, and on-device ML graphs for mobile and desktop.

Alibaba’s lightweight inference engine for mobile and edge—used for on-device LLMs and classic CV models with aggressive optimization.