Chinese verb-resultative complement construction (VRCC), constitute a distinctive syntactic-semantic pattern in Chinese that integrates agent-patient dynamics with real-world state changes; yet widely used benchmarks such as CLiMP and ZhoBLiMP provide few minimal-pair probes tailored to these constructions. We introduce ZhVrcMP, a 1,204 pair dataset spanning two paradigms: resultative complement presence versus absence, and verb–complement order. The examples are drawn from Modern Chinese and are annotated for linguistic validity. Using mean log probability scoring, we evaluate Zh-Pythia models (14M-1.4B) and Mistral-7B-Instruct-v0.3. Larger Zh-Pythia models perform strongly, especially on the order paradigm, reaching 89.87% accuracy. Mistral-7B-Instruct-v0.3 shows lower perplexity yet overall weaker accuracy, underscoring the remaining difficulty of modeling constructional semantics in Chinese.