omniASR LLM 7B v2
Meta
Speech to textTranscribes a recording into words
- Type
- Proprietary
- Input
- None held
- Output
- None held
- Cached
- None held
We don't hold a list price for this model yet · hosted only — we hold no downloadable copy
Our take
We have not written a summary of this model yet.
How good is it?
TranscriptionTurning speech into text2 of 5Open ASR WER · 60th of 74
93.1%
Misses roughly one word in 15, averaged over nine English test sets.
143×53rd of 62
an hour of audio in 25 seconds, on the board's own hardware. Your machine will differ.
1676
Stated by the leaderboard; we do not hold the list itself.
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.
Where to get it
We hold no priced listing for omniASR LLM 7B v2.
There is no copy to download and no host in our price data, so Meta is where to look. We watch OpenRouter, the provider APIs we track and the LiteLLM price set; this version appears in none of them, which is a gap in what we collect rather than a statement about what Meta sells.
When we formed this view
Dates behind this page
Prices last checked 6h ago
What we do not know about this model yet
- Nothing we hold says whether an endpoint streams, so we do not show it either way.
- We don't hold a list price for this model yet — the gap is ours, not the lab's.
Licence and identifiers
What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.
Licence
Commercial API terms. We hold no licence record for this model, so there is nothing to summarise here.
Identifiers
- Modality record
- audio->text
- Catalogue slug
- facebook-omniasr-llm-7b-v2