Open speech recognition stopped being a Whisper monoculture some time in the last twelve months. In March 2026 Cohere released Transcribe, a 2B Apache 2.0 model that took the top of the Hugging Face Open ASR Leaderboard at 5.42% average word error rate. Five weeks later IBM shipped Granite Speech 4.1 2B at 5.33%. Since then ARK-ASR-3B and MOSS-Transcribe-preview-2B have posted lower numbers still.
The top of that leaderboard is now separated by less than one WER point. That has a specific consequence for anyone choosing a model: rank is no longer the deciding variable. License, language coverage, streaming support, and cost per audio-hour are. This roundup compares the field on all four.
First, a problem with the leaderboard number everyone quotes
The Open ASR Leaderboard average is not a single fixed quantity, and the models currently listed side by side were not all scored the same way.
Cohere’s 5.42% is an average across eight English test sets, including TED-LIUM. That checks out: AMI 8.13, Earnings-22 10.86, GigaSpeech 9.34, LibriSpeech clean 1.25, LibriSpeech other 2.37, SPGISpeech 3.08, TED-LIUM 2.49, VoxPopuli 5.87 averages to exactly 5.42.
