Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4 (LLM part) failed to convert to TensorRT Engine

Describe the bug

During the model conversion of Nemotron Omni from ONNX to TensorRT Engine on the target platform, the error message shows:

...
[07:48:03.497] [INFO] [TensorRT] Successfully created plugin: Nvfp4MoePlugin
[07:48:03.516] [INFO] [llmBuilder.cpp:118:build] Created directory Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4/omni_engine_nvfp4.trtedgellm070/llm for saving LLM engine.
[07:48:03.546] [ERROR] [TensorRT] IBuilder::buildSerializedNetwork: Error Code 9: API Usage Error (INT8 and FP8 mixed precision is allowed only when building network with kSTRONGLY_TYPED mode on Blackwell+ platforms.)
[07:48:03.546] [ERROR] [builderUtils.cpp:313:buildAndSerializeEngine] Failed to build serialized engine
[07:48:04.430] [ERROR] [llm_build.cpp:242:main] Failed to build LLM engine.

Steps/Code to reproduce bug

1. Download model from https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4
2. Change model_type in config.json from NemotronH_Nano_Omni_Reasoning_V3 to NemotronH_Nano_VL_V2
3. Convert model to ONNX by using experimental llm_loader
4. Send model & cross-compiled TensorRT Edge-LLM program to Nvidia Drive Thor U (DriveOS 7.0.3)
5. Set /proc/sys/vm/nr_hugepages to 16384
6. Run ./build/examples/llm/llm_build --onnxDir Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4/omni_onnx_nvfp4.trtedgellm070/llm/ --engineDir Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4/omni_engine_nvfp4.trtedgellm070/llm

Build configuration:

cmake .. \
    -DCMAKE_BUILD_TYPE=Release \
    -DTRT_PACKAGE_DIR=/usr \
    -DCMAKE_TOOLCHAIN_FILE=cmake/aarch64_linux_toolchain.cmake \
    -DEMBEDDED_TARGET=auto-thor \
    -DCUDA_CTK_VERSION=12.8

Expected behavior

The LLM build should be completed. And I can run this omni model with llm_inference

System information (Edge Device)

• Platform (e.g., NVIDIA Jetson Thor): Drive Thor U
• Software release (e.g., JetPack 7.1): DriveOS 7.0.3
• CPU architecture: aarch64
• GPU compute capability (e.g., SM110 for Jetson Thor): SM101
• Total device memory: 59045MB
• Build type (e.g., Release, Debug): Release
• Library versions:
  • TensorRT Edge-LLM version or commit hash: 0.7.0
  • CUDA: 12.8
  • TensorRT: 10.10
  • C++ compiler (e.g., GCC 11.4): GCC 13.3 (x86 docker dev env)