Audio8 ASR 0.1B
AutoArk AI · released Jul 10, 2026 · AutoArk-AI/Audio8-ASR-0.1B
Speech to textTranscribes a recording into words
- Type
- Open weightsCreative Commons Attribution-NonCommercial 4.0
- Languages
- 7
- Size
- 0.3B
Context measured in tokens
Our take
Written Aug 3, 2026Audio8 ASR is a tiny downloadable speech-to-text model from AutoArk AI that can transcribe an hour of audio in about five seconds. It is built for research and non-commercial experiments, with accuracy that holds up on clean recordings but falls apart on harder real-world audio.
Pick this for research on tiny-model speech recognition, or for fast transcription of clean read-aloud and financial calls where roughly one word in forty wrong is acceptable. Skip it if you need commercial use, work with accented speakers or meeting recordings, or want hosted inference rather than running it yourself.
The case for it
- Extremely fast: 709 times real time on benchmark hardware, turning an hour of audio into roughly five seconds of processing.
- Strong on clean, structured audio, with 2.7% of words wrong on read-aloud and 3.73% on financial calls.
- European-accented speech at 4.39% word error rate, handled markedly better than its 12.31% rate on general accented speech.
The case against it
- Accuracy collapses on challenging real-world audio: 10.99% of words wrong in meetings and 12.31% on accented speech, up to 4.6 times worse than its clean-speech performance.
- No commercial deployment path: zero tracked offers and a Creative Commons NonCommercial licence that prohibits commercial use.
How good is it?
TranscriptionTurning speech into text2 of 5Open ASR WER · 62nd of 74
93%
Misses roughly one word in 14, averaged over nine English test sets.
709×33rd of 62
an hour of audio in 5 seconds, on the board's own hardware. Your machine will differ.
7
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 · Chinese · French · Japanese · Cantonese · German · Korean
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. 21.4 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. 22.6 GB spare means a 10% error in the size would not change the answer.
Apple M1 (8-core GPU, 8GB unified) · 8 GB
Room to spare. 4.6 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 →
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-NonCommercial 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-NonCommercial 4.0
Weights are downloadable but commercial use is prohibited. Research and personal use only.
Identifiers
- Hugging Face
- AutoArk-AI/Audio8-ASR-0.1B
- Architecture
- Dense
- Modality record
- audio->text
- Catalogue slug
- autoark-ai-audio8-asr-0-1b