Granite Speech 3.3 8b
IBM · released Apr 14, 2025 · ibm-granite/granite-speech-3.3-8b
Speech to textTranscribes a recording into words
- Type
- Open weightsApache License 2.0
- Languages
- 5
- Size
- 8.6B
Context measured in tokens
Our take
Written Aug 2, 2026Granite Speech 3.3 is an Apache-licensed speech-to-text model from IBM that turns audio into written text. It is extremely fast on batch workloads and near-perfect on clean read-aloud English, though its accuracy widens sharply on harder audio and no hosted providers currently offer it.
Pick this for high-throughput batch transcription of clean English audio where you need a permissive licence, or for regulated environments that require Apache-licensed self-hosted deployment. Skip it if you are transcribing meetings, podcasts, accented speech or video; if you need hosted inference; or if you need verified accuracy in French, German, Spanish or Portuguese.
The case for it
- Extremely fast batch transcription at 264 times real time — an hour of audio in 14 seconds on the leaderboard's own hardware.
- Truly permissive Apache 2.0 licence allows commercial use, modification and redistribution.
- Near-perfect on clean read-aloud English, with about one word in ninety wrong.
- Five languages supported: English, French, German, Spanish and Portuguese.
The case against it
- Accuracy collapses on challenging audio: podcasts, video and accented speech are more than eight times worse than clean read speech, and recorded meetings are seven times worse.
- No hosted offers available; you must self-host.
- Every accuracy figure is English only; nothing we hold measures the other four languages.
How good is it?
TranscriptionTurning speech into text3.5 of 5Open ASR WER · 25th of 74
94.7%
Misses roughly one word in 19, averaged over nine English test sets.
264×46th of 62
an hour of audio in 14 seconds, on the board's own hardware. Your machine will differ.
5
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 · French · German · Spanish · Portuguese
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. 15.7 GB spare means a 10% error in the size would not change the answer.
GeForce RTX 5090 · 32 GB
Room to spare. 23.7 GB spare means a 10% error in the size would not change the answer.
Apple M1 (8-core GPU) · 16 GB
Room to spare. 4.9 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 Granite Speech 3.3 8b
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
- ibm-granite/granite-speech-3.3-8b
- Architecture
- Dense
- Modality record
- audio->text
- Catalogue slug
- ibm-granite-granite-speech-3-3-8b