Higgs Audio v3 8b STT v2
Boson AI · released Apr 27, 2026 · bosonai/higgs-audio-v3-8b-stt-v2
Speech to textTranscribes a recording into words
- Type
- Open weightsApache License 2.0
- Languages
- 1
- Size
- 8.9B
Context measured in tokens
Our take
Written Aug 2, 2026Higgs Audio is an English-only speech-to-text model from Boson AI that turns audio into written words at exceptional speed. It achieves near-perfect accuracy on clean read-aloud recordings, but its error rate rises sharply on accented speech or meeting audio.
Pick this for high-throughput transcription of clean English audio where speed matters, or for self-hosted deployment needing a permissive licence. Skip it if your audio includes accented speakers or meetings, if you need non-English languages, or if you require hosted inference.
The case for it
- Extremely fast: 139.1 times real time on benchmark hardware, or roughly an hour of audio in 26 seconds.
- Near-perfect on clean read-aloud English: 0.95% word error rate, roughly one word wrong per 105.
- Apache 2.0 licence allows commercial use, modification and redistribution.
The case against it
- Accuracy collapses in challenging conditions: 8.45% on accented speech and 8.37% in meetings — roughly eight to nine times worse than on clean read-aloud.
- No hosted availability in our catalogue; must be self-hosted or sourced outside our data.
- English only; no source we hold measures accuracy in any other language.
How good is it?
TranscriptionTurning speech into text4.5 of 5Open ASR WER · 11th of 74
95.3%
Misses roughly one word in 21, averaged over nine English test sets.
139×55th of 62
an hour of audio in 26 seconds, on the board's own hardware. Your machine will differ.
1
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.
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. 15.5 GB spare means a 10% error in the size would not change the answer.
GeForce RTX 5090 · 32 GB
Room to spare. 23.5 GB spare means a 10% error in the size would not change the answer.
Apple M1 (8-core GPU) · 16 GB
Room to spare. 4.7 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 Higgs Audio v3 8b STT v2
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 allowsApache License 2.0, 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
Apache License 2.0
Fully permissive: commercial use, redistribution, and derivatives allowed. Requires attribution and a copy of the license. Includes an express patent grant.
Identifiers
- Hugging Face
- bosonai/higgs-audio-v3-8b-stt-v2
- Architecture
- Dense
- Modality record
- audio->text
- Catalogue slug
- bosonai-higgs-audio-v3-8b-stt-v2