# Next Steps

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/)
- [Understand Mixture of Experts architecture for edge deployment](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/1_mixture_of_experts/)
- [Set up llama.cpp on an Armv9 development board](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/2_llamacpp_installation/)
- [Compare ERNIE model behavior and expert routing](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/3_ernie_moe/)
- [Optimize performance with Armv9 hardware features](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/4_v9_optimization/)
- [Next Steps](https://learn.arm.com/learning-paths/cross-platform/ernie_moe_v9/_next-steps/)

## Continue Learning

### Read related resources
Find more information about the topics in this Learning Path:

- [ERNIE-4.5-21B Modelscope](https://modelscope.cn/models/unsloth/ERNIE-4.5-21B-A3B-PT-GGUF)
- [llama.cpp GitHub repository](https://github.com/ggml-org/llama.cpp)
- [Build and run llama.cpp with Arm CPU optimizations](https://learn.arm.com/learning-paths/servers-and-cloud-computing/llama_cpp_streamline/)

### Join the Arm Developer Program
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