AMD-AGI/AgentKernelArena

AgentKernelArena targets a highly specialized niche: evaluating how well AI agents (like Claude Code or SWE-agent) can write and optimize low-level GPU kernels (CUDA/HIP/Triton). While general code-gen benchmarks like SWE-bench exist, this project focuses on the hardware-software interface which is increasingly critical for AI infrastructure. However, the project currently lacks significant traction, with only 13 stars and stagnant velocity over its 3-month lifespan. Its defensibility is low because the 'moat' consists primarily of the curated set of kernel tasks and the sandboxing harness, both of which are reproducible by well-funded labs or hardware incumbents. The platform domination risk is high as NVIDIA or AMD (who owns the repo's parent org) could easily release more robust, first-party evaluation suites for their respective ecosystems. It serves as a valuable reference implementation for how to evaluate agents in HPC contexts but lacks the community scale to become a de facto standard yet.