Sarvam AI and AI4Bharat released Indic DiarBench, an open Hugging Face dataset of about 108 hours of natural multi-speaker speech across all 22 scheduled Indian languages. It jointly scores ASR and speaker diarization with human-verified, speaker-attributed transcripts from meetings and in-the-wild audio, targeting overlaps and code-mixing that single-speaker tests miss. Sarvam says Indic-specialized pipelines lead commercial APIs on the joint metrics. That matters for tools that must know who said what. The caveat is that lab scores still need to hold on noisier telephony.