OpenAI released two speech recognition models, GPT Transcribe and GPT Live Transcribe, cutting file transcription costs 25% and scoring 3.31% on an independent accuracy benchmark. GPT Transcribe scored a 3.31% word error rate on the AA-WER index, ninth among the systems tracked. File transcription now costs $0.0045 per minute, 25% below GPT-4o Transcribe, while streaming costs $0.017. Both models take written context, keyword lists and language hints to sharpen accuracy on noisy audio. The company introduced both models through its developer platform on Jul. 28, then published model pages, a rewritten transcription guide and code samples for every supported endpoint. GPT Transcribe covers completed audio files and heavier batch work, moving through recordings at roughly 34 times real time. GPT Live Transcribe streams text back over an open connection while a person is still talking. Microsoft has already listed both versions inside its own Foundry platform. Context lifted semantic accuracy on OpenAI's own benchmark from 41.6% to 45.2%. Artificial Analysis measured GPT Transcribe at a 3.31% word error rate on its AA-WER index, placing it ninth among the roughly 50 systems the firm currently tracks, a gain of 0.7 percentage points on GPT-4o Transcribe, although the model scored 6.10% on earnings calls. Across 22 languages on Common Voice, OpenAI logged 19.27