Soniox has released Soniox v5 Real-Time： a low latency streaming Speech to Text model on the Pareto frontier for accuracy and latency， at the lowest price of any proprietary model tested

Soniox v5 Real-Time is @soniox_ai's latest streaming Speech to Text （STT） model， joining Soniox v5 Async， their non-streaming model released last week. On AA-WER Streaming it occupies the middle of the Pareto frontier： faster than the most accurate models （Cartesia Ink-2， ElevenLabs Scribe v2 Realtime） and more accurate than the fastest （Deepgram Flux， Nova-3）， while at a lower price than all of them.

AA-WER Streaming Overview

AA-WER Streaming reports WER and latency as a pair， measured from Silero VAD-detected end of speech on the same ~8 hours of audio as our non-streaming STT benchmark， AA-WER v2.0. We report both at two points： First Final （first final-denoted transcript， best for accuracy） and First Partial （first transcript-bearing event， best for when speed matters most）.

Key takeaways

➤ First Final Transcription： Soniox v5 Real-Time achieves a 4.5% WER at 0.05s after end of speech， more accurate than the faster Deepgram Flux （7.4%， 0.02s） and Deepgram Nova-3 Realtime （6.7%， 0.06s）， and faster than the more accurate Cartesia Ink-2 external endpoints （3.7%， 0.09s） and ElevenLabs Scribe v2 Realtime （3.6%， 0.14s）

➤ First Partial Transcription： The model achieves a 4.7% WER at 0.05s after end of speech， behind only Cartesia Ink-2 external endpoints （4.3%， 0.07s） and ElevenLabs Scribe v2 Realtime （3.6%， 0.13s） on accuracy， while faster than both

➤ Price： The model costs $2 per 1，000 minutes representing the lowest of any proprietary streaming model tested， below Cartesia Ink-2 （$4）， Deepgram Nova-3 Realtime （$4.80） and ElevenLabs Scribe v2 Realtime （$6.50）