SOURCE-LINKED INTELLIGENCE

TicTacBench: Benchmarking Timing Closure Capabilities of Coding Agents

arXiv · AI, language, vision and robotics · article · Sep 20, 2026 · UTC

Recent advances in large language models (LLMs) have led to the emergence of coding agents capable of performing complex engineering tasks, including register-transfer level (RTL) design and optimization. Existing RTL benchmarks mainly evaluate functional correctness and performance, power, and area (PPA) of the generated RTL designs, leaving agents' ability for \emph{timing closure} under-evaluated. We propose TicTacBench, a benchmark specifically designed to evaluate coding agents' capabilities for RTL-level timing closure under post-place-and-route (post-PnR) evaluation. TicTacBench contain

Read original source ↗ Open in workspace

recordType

paper

region

Global