MMed-Bench-IR introduces a heterogeneous benchmark for multilingual medical information retrieval across six languages. It evaluates cross-lingual alignment, concept discrimination, and evidence retrieval through three distinct tasks with no overlapping concepts or queries. Evaluation shows significant cross-lingual performance drops, with English biomedical encoders falling from 0.818 to 0.056 nDCG@10 when transitioning to Japanese, highlighting limitations undetected by English-only benchmarks.