ggml : add NVFP4 quantization type support

It's available b8297 onwards. Get latest llama.cpp version.

This adds support for NVIDIA's NVFP4 quantization format (FP4 E2M1 weights, UE4M3 per-block scale, 16 elements per block). This is the format produced by NVIDIA ModelOpt's NVFP4 algo. The main difference is the scale encoding (UE4M3 vs E8M0).

What's in here:

New GGML_TYPE_NVFP4 type, block struct, UE4M3 conversion helpers, reference quantize/dequantize

convert_hf_to_gguf.py detects NVFP4 ModelOpt models and repacks into the GGUF block format

CPU backend: scalar dot product + ARM NEON

gguf-py: type constant, quant/dequant, endian conversion

Tests added to test-backend-ops and test-quantize-fns

Tested with models from https://huggingface.co/NVFP4 Apple M5 MacBook (CPU, NEON) Ran llama-bench and a basic server smoke test. Would appreciate help with that if someone has a good baseline to compare against.

Here is a Qwen3-4B model to test with.