Canary 1b Flash
NVIDIA · nvidia/canary-1b-flash
Speech to textTranscribes a recording into words
- Type
- Open weightsCreative Commons Attribution 4.0
- Languages
- 4
- Size
- 1B
Context measured in tokens
Our take
Written Aug 2, 2026Canary 1b Flash is NVIDIA's tiny downloadable speech-to-text model that turns audio into written words. It is extremely fast and near-perfect on clean recordings, but accuracy drops sharply on messy real-world audio and no hosts currently offer it.
Pick this for lightning-fast batch transcription of clean audio, where it processes an hour of speech in about two seconds. Use it for financial call transcription or lightweight local deployment. Skip it if your audio is messy, accented, or from recorded meetings, where error rates rise tenfold; or if you need hosted inference.
The case for it
- Processes audio at over two-thousand-times real time — an hour of audio in roughly two seconds on benchmark hardware.
- Near-perfect on clean read-aloud audio at 1.2% word error rate, and strong on financial calls at 1.75%.
- Creative Commons Attribution 4.0 licence allows commercial use with attribution.
- European-accented speech is handled at 4.17% error, roughly three times better than its overall accented-speech rate.
The case against it
- Accuracy collapses on messy real-world audio: recorded meetings hit 10.58% error, podcasts and video 8.19%, and accented speech overall 12.03%.
- No hosted inference options are currently tracked.
- Only four languages are listed, and all accuracy figures are English-only; German, Spanish and French are unverified.
How good is it?
TranscriptionTurning speech into text3 of 5Open ASR WER · 39th of 74
94.2%
Misses roughly one word in 17, averaged over nine English test sets.
2,126×18th of 62
an hour of audio in 2 seconds, on the board's own hardware. Your machine will differ.
4
Listed on the model card. The accuracy above is English only.
Percentage of words wrong on each set, lower better. Bars are scaled to this model's own worst case, not to the board.
Which languages ↓ ↑
English · German · Spanish · French
The figures above come from the Open ASR Leaderboard, an independent public test that runs every model on the same recordings. It is the only measurement of transcription quality we know of, so there are no other scores to show.
These tests check whether a model follows instructions — a precondition for all the work above, but not a measure of how well that work is done, which is why they get no rating.
Every published score for this model9 scoresEvery figure we hold, from 9 boards, with who ran it and a link to the source — including the boards no rating above is built on.
Can you run it yourself?
- Fits in memory
- weights load entirely on the card
- Spills to system RAM
- some weights offload; much slower
- Too large
- will not load even with offload
- est
- size is calculated; the verdict could change by 10%
Comfortable fit
GeForce RTX 4090 · 24 GB
Room to spare. 20.9 GB spare means a 10% error in the size would not change the answer.
Apple M1 Pro (16-core GPU) · 32 GB
Room to spare. 22.1 GB spare means a 10% error in the size would not change the answer.
Apple M2 (8-core GPU, 8GB unified) · 8 GB
Room to spare. 4.1 GB spare means a 10% error in the size would not change the answer.
Memory use by level
Against a 24 GB card.
All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.
Check against your own machine → · All 71 devices, with every size →
Models people weigh against Canary 1b Flash
When we formed this view
Dates behind this page
Prices last checked 6h ago
What we do not know about this model yet
- We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
Licence and identifiers
What the licence allowsCreative Commons Attribution 4.0, what it allows commercially, and the identifiers you need to pull this model — its Hugging Face repo, our slug and a machine-readable card.
Licence
Creative Commons Attribution 4.0
Permissive content license: any use with attribution. Common for datasets and some model weights.
Identifiers
- Hugging Face
- nvidia/canary-1b-flash
- Modality record
- audio->text
- Catalogue slug
- nvidia-canary-1b-flash