Welcome to the Arm AI Optimization Challenge 2026. We’re inviting developers to build and submit projects that show how AI can be optimized for Arm-powered platforms across three challenge tracks: Physical AI: Optimize AI for real-world systems, including robotics, embedded devices, sensors, simulation, autonomy, and edge environments. Cloud AI: Optimize AI for scalable infrastructure, including Arm64 cloud, inference performance, frameworks, agents, and production-ready developer workflows. Mobile AI: Optimize AI for on-device constraints, including performance, privacy, latency, battery efficiency, and local AI experiences on Arm-powered phones, tablets, and laptops. Across all tracks, submissions should show clear optimization work and measurable improvements where possible. Optimizations we will look for: Model size: Reduce size on disk or in memory. Model quality: Improve fine-tuning or output quality for a given model size. Model speed: Improve tokens/sec, time to first token, or other relevant latency metrics. Inference server speed: Improve throughput, latency, tokens/sec, or time to first token. Developer experience: Improve tools, workflows, setup, documentation, or usability. Arm-specific optimization: Implement optimizations in an existing framework, library, model, or application to run better on Arm. Developers can use Arm Performix to get exact benchmarks of their Arm based performance and be able to clearly show their results.
