Gemma4-VL: add gemma4_e2b_qat_vl_vision

Gemma4-VL: add gemma4_e2b_qat_vl_decode_int4linsym_aotc_h18p

Gemma4-VL: add gemma4_e2b_qat_vl_decode_int4linsym

Gemma4-VL: add gemma4_e2b_qat_vl_decode_int4linsym_tbl

E2B QAT gather tables (checkpoint-derived - pair with the QAT bundles)

E2B QAT tbl bundle, precompiled h18p .aimodelc

E2B official-QAT int4lin tbl bundle (Mac 78.9, iPhone 30.7 tok/s)

gemma4 e2b int4lin tbl AOT h18p bundle (CoreAIChat Gemma ⚡ download target)

gpu-pipelined: gemma4 int4lin tbl bundle (PLE table as static graph input; M4 Max 77.0, iPhone 30.3 via AOT)

macOS best: head+argmax kernel (int8)

macOS best: int8 fused-kernel core (56.6-59 tok/s)

macOS best: gather front-end (.aimodel, int8)

iOS ANE best: head with in-graph argmax (int8)

iOS ANE best: chunk 6/6 (int8, fp16-hardened)

iOS ANE best: chunk 5/6 (int8, fp16-hardened)

iOS ANE best: chunk 4/6 (int8, fp16-hardened)

iOS ANE best: chunk 3/6 (int8, fp16-hardened)

iOS ANE best: chunk 2/6 (int8, fp16-hardened)

iOS ANE best: chunk 1/6 (int8, fp16-hardened)

mmap gather front-end tables (shared: iOS GPU + iOS ANE)

iOS GPU best: int4-kmeans head+argmax kernel

iOS GPU best: int4-kmeans fused-kernel core (17.7 tok/s)

initial commit