SpaceXAI Releases Grok Voice Transcribe 2.0: A Speech-to-Text API Claiming 2x Accuracy Over 1.0 at $0.10 per Hour

來源原標題

SpaceXAI Releases Grok Voice Transcribe 2.0: A Speech-to-Text API Claiming 2x Accuracy Over 1.0 at $0.10 per Hour

作者

Michal Sutter

原始標籤

AI Shorts · Applications · Artificial Intelligence · Audio Language Model · Editors Pick · Language Model · Large Language Model · New Releases · Staff · Tech News · Technology · Uncategorized · Voice AI

原始連結

https://www.marktechpost.com/2026/09/18/spacexai-releases-grok-voice-transcribe-2-0/

摘要原文

SpaceXAI has released Grok Voice Transcribe 2.0 , its newest speech-to-text (STT) model. The development team claims it to be twice as accurate as Grok Voice Transcribe 1.0 at the same price. The model targets hard audio: noisy phone lines, competing voices, local accents, and spoken credentials. It runs in batch and real-time streaming modes through the Speech to Text API . Is it deployable? Yes, as a hosted API. It is live today under the model ID grok-voice-transcribe-2.0 . SpaceXAI has not announced open weights, so self-hosting is not an option. Grok Voice Transcribe 2.0 is built on the audio foundation model behind Grok Voice. SpaceXAI team states that Grok Voice already handles tens of thousands of customer-support calls a day. It also transcribes millions of hours of video narration and runs the Grok assistant in Tesla vehicles. The training data is live, noisy, multilingual audio recorded across diverse environments. SpaceXAI then refined the model with post-training. SpaceXAI reports a first-place accuracy rank among 32 streaming models on the public Artificial Analysis leaderboard . That benchmark, AA-WER Streaming, uses about 8 hours of audio. It weights AA-AgentTalk at 50%, VoxPopuli at 25%, and Earnings22 at 25%. See the methodology for details. SpaceXAI also measures word error rate (WER) on 4 internal sets drawn from production traffic: Version 2.0 improves on 1.0 across all 4 sets. On telephony, SpaceXAI says it leads every model the company tested. These internal results are vendor-reported and not independently reproduced. The model transcribes dozens of languages and detects the language automatically. It also follows mid-recording language switches in a single pass. SpaceXAI team calls multilingual accuracy the largest improvement over 1.0. Short phrases, such as in-car commands, give a model little context to identify the language. On that set, WER drops from 20.6% to 6.8%. That works out to roughly 67% fewer word errors. The docs list 25 languages for written-form formatting of numbers, currencies, and units. Every feature below ships in the same API: The batch endpoint accepts files up to 500 MB across 12 audio formats. Streaming also accepts Opus at roughly 4 KB/s, versus 48 KB/s for raw PCM at 24 kHz. Pricing is identical to version 1.0. Batch transcription costs $0.10 per hour of audio. Streaming costs $0.20 per hour. Diarization, timestamps, and key terms are included. That equals about $1.67 and $3.33 per 1,000 minutes. Atlassian Loom now uses Grok Voice Transcribe 2.0 to transcribe every video. Atlassian found it more accurate than its existing solution. The workflow SpaceXAI describes is record, transcribe, then code. A user records an action plan in Loom. The transcript is piped into Cursor , which makes the code updates. Sanchan Saxena, SVP of Teamwork Collection at Atlassian, described it as ‘closing the loop from context to code.’ Check out the technical details and the API docs . All credit goes to the researcher of this project. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter . Wait! are you on telegram? now you can join us on telegram as well. Need to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? Connect with us The post SpaceXAI Releases Grok Voice Transcribe 2.0: A Speech-to-Text API Claiming 2x Accuracy Over 1.0 at $0.10 per Hour appeared first on MarkTechPost .