Speech to text models and APIs.

Multilingual speech-to-text for 25 European languages with auto language detection, punctuation, capitalization, and optional timestamps.

CohereLabs cohere-transcribe-03-2026 is a 2B Conformer speech-to-text model for 14 languages. It creates accurate transcripts for meetings, calls, and audio archives.

A lightweight speech-to-text model optimized for fast inference. Converts audio input into text with support for multiple languages.

Voxtral Mini 4B Realtime 2602 is a multilingual, realtime speech-transcription model and among the first open-source solutions to achieve accuracy comparable to offline systems with a delay of <500ms. It supports 13 languages and outperforms existing open-source baselines across a range of tasks, making it ideal for applications like voice assistants and live subtitling.

Nemotron-Speech-Streaming-En-0.6b is the first unified model in the Nemotron Speech family, engineered to deliver high-quality English transcription across both low-latency streaming and high-throughput batch workloads. The model natively supports punctuation and capitalization and offers runtime flexibility with configurable chunk sizes, including 80ms, 160ms, 560ms, and 1120ms.

Speech to text model from ElevenLabs

OpenAI Whisper Medium transcribes speech to text with timestamps and optional speaker diarization. Works across many languages and noisy audio.

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without the need for fine-tuning.

Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. Trained on 680k hours of labelled data, Whisper models demonstrate a strong ability to generalise to many datasets and domains without the need for fine-tuning.