AgentKernelArena
by AMD-AGI
Side-by-side GPU kernel benchmarking for LLM agents
Overview
Provides an end-to-end, siloed benchmarking arena to evaluate different LLM-powered agents on identical GPU kernel tasks. Runs agents such as Cursor Agent, Claude Code, Codex and others side-by-side and collects objective, reproducible metrics for direct comparison. Includes tooling to isolate kernels, standardize inputs, and measure performance, correctness, and resource use across models. This framework supports A2A Protocol Pattern for multi-agent orchestration and aligns with Open Agent Specification (Agent Spec).
Key Benefits
Ideal For
Researchers and engineers who need reproducible, GPU-level comparisons of LLM-powered agents to build agent track records and evaluate failure modes. For structured evaluation guidance, consider the LLM-as-Judge Pattern to formalize how LLMs can assess agent outputs, and explore the Event-Driven Agent Pattern for scalable orchestration of agent tasks.
Real-World Examples
- When you need reproducible, kernel-level comparisons of different LLM agents on the same tasks
- When you need to measure agent reliability, performance, and resource usage under identical GPU conditions
- When you want to generate objective metrics to feed an agent reputation or RepKit system