AgentKernelArena - Triton-to-Triton: leaderboard

GPU kernel optimization by coding agents on AMD Instinct MI300X from AgentKernelArena (Younesian et al., AMD, 2026): agents speed up 148 Triton kernels from the vLLM inference engine and ROCmBench against the unmodified kernels, working in an isolated workspace with compile, correctness and performance gates. Mean per-task speedup (a ratio, unbounded above), with failed compilation or correctness counted as 0, averaged over three runs; higher is better.

Metric: Mean speedup (x; arithmetic mean over the 148 Triton-to-Triton tasks (118 vLLM, 30 ROCmBench kernels) of the per-task speedup over the unmodified Triton kernel, counting 0 for a task whose kernel fails compilation or correctness; per-task mean of 3 runs; agent in an isolated workspace, 3600 s timeout, up to 3 kernel versions; AMD Instinct MI300X). Source: arxiv.org. Saturation forecast: Around August 2027. 8 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 4.7 (High)2.13#75 (Claude Opus 4.7)
2Claude Opus 4.62.11#100
3Claude Sonnet 4.62#158
4GPT-5.4 (High)1.75#121 (GPT-5.4)
5Claude Opus 4.6 (High)1.73#100 (Claude Opus 4.6)
6GPT-5.3 Codex1.68#114
7GPT-5.3 Codex (High)1.65#114 (GPT-5.3 Codex)

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=agentkernelarena-triton-to-triton · How It Works · Data refreshed daily, snapshot 2026-11-12.