Transcribe with NVIDIA Canary
3.5%
WER
4
Languages
45.0x
Speed
CC-BY-4.0
License
About NVIDIA Canary
NVIDIA Canary is a 1B parameter model that excels at English, German, French, and Spanish transcription. Built on the NeMo framework, it uses a FastConformer encoder with a transformer decoder and supports automatic language detection and translation.
Model Info
- ProviderNVIDIA
- Architecture-
- LicenseCC-BY-4.0
- UpdatedMar 2026
Frequently Asked Questions
NVIDIA Canary is a speech-to-text model by NVIDIA. STT.ai hosts NVIDIA Canary on our GPU infrastructure so you can use it without provisioning your own hardware — upload audio or video and pick NVIDIA Canary from the model picker.
On standard benchmarks, NVIDIA Canary achieves around 3.5% Word Error Rate. Real-world accuracy depends on audio quality, accent, and language; for noisy or accented recordings, expect a few percentage points higher WER.
NVIDIA Canary runs on STT.ai's free tier — every visitor gets 600 minutes/month at no cost. Paid plans add longer per-file limits, private transcripts, and priority queueing.
NVIDIA Canary is released under CC-BY-4.0, a permissive open-source license. You can self-host NVIDIA Canary on your own hardware or use our hosted version — both are commercially usable.
NVIDIA Canary supports 4 languages. Auto-detection picks the right language for most audio; you can also specify it manually for a small accuracy lift.
NVIDIA Canary processes audio at about 45.0x real-time on our GPUs. A 1-hour audio file finishes in under 1 minutes; longer files queue and notify by email when done.
NVIDIA Canary has 1B parameters. Larger models tend to be more accurate but slower; STT.ai hosts NVIDIA Canary on GPU so the parameter count doesn't affect your client-side performance.
NVIDIA Canary accepts every format STT.ai supports — MP3, WAV, M4A, FLAC, OGG, MP4, MKV, MOV, WebM, AVI, and others. Output as TXT, SRT, VTT, DOCX, JSON, or PDF.
Yes. Speaker diarization runs alongside NVIDIA Canary for every transcription — each speaker is labeled and you can rename them in the editor afterwards.
Yes. NVIDIA Canary runs in our managed environment — audio is processed and deleted by default and never used for training without explicit opt-in. Pro plans add client-side encryption for transcripts at rest.
Use the compare-stt tool to run NVIDIA Canary against any other supported model on the same audio — you'll see WER, segment count, speaker labels, and confidence scores side-by-side. The NVIDIA Canary vs Whisper Large V3 comparison is the most commonly run.
Yes. Specify "nvidia-canary" as the model parameter on the /v1/transcribe endpoint. Python and Node.js SDKs include NVIDIA Canary examples. Free API tier includes 100 minutes/month.
Yes. Because NVIDIA Canary is CC-BY-4.0-licensed, you can self-host it. STT.ai's open-source page lists the project repo and weights. Most production teams use our hosted version to skip GPU procurement, model swaps, and ops.