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Parakeet TDT 0.6B v3

Parakeet TDT 0.6B v3

0.6B v3 · Family: Parakeet
NVIDIA's multilingual ASR model (600M parameters, FastConformer-TDT) transcribing speech in 25 European languages with automatic language detection.
✓ Active✓ Public access⚖ Open weightsAudio📁 Parakeet
Parameters
0.6B (600M)
parameters
Release date
14 August 2025
Access:DownloadHostedDeployment:💻 Local☁ Cloud

Overview

Parakeet TDT 0.6B v3 is a 600-million-parameter multilingual automatic speech recognition (ASR) model developed by NVIDIA and released in August 2025. It extends its predecessor parakeet-tdt-0.6b-v2 from English to 25 European languages, automatically detecting the spoken language without additional prompting.

The architecture combines a FastConformer encoder with a Token-and-Duration Transducer (TDT) decoder. The model adds automatic punctuation and capitalization, produces word- and segment-level timestamps, and supports long-form audio — up to 24 minutes with full attention (on an A100 80GB GPU) or up to 3 hours with local attention. Input is 16 kHz mono audio (.wav, .flac); output is text.

The model was trained on a combination of the Granary dataset's ASR subset (about 660,000 hours of pseudo-labeled data) and the in-house NeMo ASR Set 3.0 (about 10,000 hours of human-transcribed data). It is part of the Parakeet family within the NVIDIA NeMo toolkit and is released under the CC BY 4.0 license for commercial and non-commercial use.

Classification
Audio
Family: Parakeet
Access & deployment
DownloadHosted
LocalCloud
Weights: Open weights
Key parameters
🧩 Parameters: 0.6B (600M)
✓ Fine-tuning
📥 Input: audio

Technical specification

Parameters
0.6B (600M)
parameters
License
CC-BY-4.0
Hardware requirements
Optimized for NVIDIA GPU accelerators (CUDA). Long-form transcription up to 24 minutes with full attention requires an A100 80GB GPU; a quantized GGUF variant (q8_0) is available for lightweight local inference via NeMo-Speech.cpp.
Features:✓ Fine-tuning
Modalities
⬇ Input
audio
⬆ Output
text

Benchmark results

10 benchmarks
LibriSpeech test-clean (WER)
WER · test, English
1.93%
📄 Model card (Hugging Face)
LibriSpeech test-other (WER)
WER · test, English
3.59%
📄 Model card (Hugging Face)
GigaSpeech (WER)
WER · test, English
9.59%
📄 Model card (Hugging Face)
AMI (Meetings, IHM) (WER)
WER · test, English
11.31%
📄 Model card (Hugging Face)
TED-LIUM v3 (WER)
WER · test, English
2.75%
📄 Model card (Hugging Face)
FLEURS English (WER)
WER · test, en_us
4.85%
📄 Model card (Hugging Face)
FLEURS German (WER)
WER · test, de_de
5.04%
📄 Model card (Hugging Face)
FLEURS Spanish (WER)
WER · test, es_419
3.45%
📄 Model card (Hugging Face)
FLEURS French (WER)
WER · test, fr_fr
5.15%
📄 Model card (Hugging Face)
FLEURS Polish (WER)
WER · test, pl_pl
7.31%
📄 Model card (Hugging Face)

Technical architecture

Core Architecture
Model Form
Training Techniques