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LatestNVIDIAv2
NVIDIASpeech → Text

NVIDIA Releases Canary 1B v2 Multilingual Speech Model

The new 1-billion-parameter model handles both transcription and translation across five languages using the company's efficient FastConformer architecture.

Aug 4, 2025
NotableCC BY 4.0
Canary 1B v2

NVIDIA has released Canary 1B v2, a versatile 1-billion-parameter model for automatic speech recognition (ASR) and translation. Published with a permissive CC-BY-4.0 license, the model provides developers with a powerful new tool for building voice-enabled applications.

The model is built on NVIDIA's FastConformer architecture, which is designed for high-performance and efficient speech processing. Canary excels at multilingual tasks, handling both transcription in a source language and translation from that language into English within a single model.

Core Capabilities

According to its official release card, Canary 1B v2 was trained to handle several key tasks without the need for separate models:

  • Transcription: Supports English, German, French, Spanish, and Mandarin.
  • Translation: Can translate any of the supported source languages into English text.
  • Formatting: Includes automatic punctuation and capitalization to produce more readable output.

This release adds another high-quality, open-source option to a field largely defined by models like OpenAI's Whisper. By providing a permissively licensed and efficient alternative, NVIDIA gives developers more flexibility for integrating advanced speech AI. The model and its usage instructions are available on NVIDIA's Hugging Face page.

Sources

  • nvidia/canary-1b-v2

    Hugging Face

    Visit
OlderNVIDIA Releases 600M Parakeet for Speech RecognitionNVIDIA · Speech → Text · last yearNewerOpenAI Releases Its First Open-Source MoE ModelOpenAI · Reasoning · last year

Get the model

Hugging Face

Specs

Parameters1B
Languages25 languages
Size3.9 GB
PrecisionFP32
ArchitectureCanaryForConditionalGeneration
LicenseCC-BY-4.0
Downloads247K
Likes447

Can you run it?

Runs on just about anything.

  • FP32 (as published)

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    4.9 GB
  • 16-bit

    Any modern laptop · 8 GB RAM

    3 GB
  • FP8

    Any modern laptop · 8 GB RAM

    2 GB
Your machine

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Speech → Text

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