Models / IBM/ Granite 4.0 1b Speech

Granite 4.0 1b Speech

IBM · released Feb 27, 2026 · ibm-granite/granite-4.0-1b-speech

Speech to textTranscribes a recording into words

Input: audio. Output: text.InputOutput
Type
Open weightsApache License 2.0
Languages
6
Size
2.3B

Context measured in tokens

Our take

Written Sep 4, 2026

Granite 4.0 is a 2.3-billion-parameter speech-to-text model from IBM with a permissive Apache licence. It is built for speed and local deployment, handling six languages and transcribing an hour of audio in about five seconds on modest hardware.

Who should pick it

Pick this for fast local transcription on limited hardware, or for meeting-room and accented speech where it outperforms most peers. Use it if you need open-weight coverage in French, German, Spanish, Portuguese or Japanese. Skip it if your source is podcasts or internet video, where it trails the field, or if you want a fully managed hosted service rather than self-hosting.

The case for it

  • Extremely fast: 661× real-time speed, turning an hour of audio into text in roughly five seconds.
  • Strong on meeting audio at 7.4% word error rate, well below the field middle of 10.6%.
  • Handles accented speech better than most, at 8.3% versus a field middle of 10.8%.
  • Apache 2.0 licence allows commercial use, modification and redistribution.

The case against it

  • Podcasts and internet video are a weak spot at 8.4% word error rate, behind the field middle of 8.2%.
  • Not the leader on clean read-aloud audio: 1.1% versus the field best of 0.9%.
  • No hosted providers tracked; you must run it yourself.
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How good is it?

An open speech-to-text model for turning recordings of meetings and clear read-aloud speech into written text.

Good at
  • transcribing recordings of meetings in a roomRecorded meetings · 14th of 92
  • transcribing clear recordings of people reading aloudClean read speech · 17th of 92

TranscriptionTurning speech into text3 of 5Open ASR WER · 38th of 76

Words it gets right

94.9%

Misses roughly one word in 20, averaged over nine English test sets.

How fast it listens

666×43rd of 74

an hour of audio in 5 seconds, on the board's own hardware. Your machine will differ.

Languages

6

Listed on the model card. The accuracy above is English only.

Where it struggles
Read aloudaudiobooks, clean recording1.1%17th of 92
Podcasts and videoeveryday internet audio8.4%53rd of 92
Accented speechspeakers from many countries8.5%48th of 76
Meetingsa room, several people, far microphone7.4%14th of 92

Percentage of words wrong on each set, lower better. Bars are scaled to this model's own worst case; the placing beneath each rate is against every model measured on that set.

Which languages ↓

English · French · German · Spanish · Portuguese · Japanese

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.

Other boards it appears on
Recorded meetings 14th of 92Clean read speech 17th of 92Harder read speech 18th of 92Podcasts and video 53rd of 92European-accented speech 71st of 92Financial calls 77th of 92Accented speech 48th of 76

Each of these is the same transcription job on a different kind of recording, so together they say where it holds up and where it slips — not how closely it follows an instruction.

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.
666.2source ↗
5.1source ↗
8.53source ↗
3.55source ↗
7.38source ↗
4.41source ↗
8.44source ↗
1.11source ↗
2.5source ↗
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Can you run it yourself?

Comfortable fit

A card many people ownFits in memory

GeForce RTX 4090 · 24 GB

Weights at 1.5 / 24 GBest
Spare memory19.9 GB spare
Usable context131Kwhat the spare memory holds; no published limit on record

Room to spare. 19.9 GB spare means a 10% error in the size would not change the answer.

One step upFits in memory

GeForce RTX 5090 · 32 GB

Weights at 1.5 / 32 GBest
Spare memory27.9 GB spare
Usable context262Kwhat the spare memory holds; no published limit on record

Room to spare. 27.9 GB spare means a 10% error in the size would not change the answer.

On a MacFits in memory

Apple M2 (8-core GPU, 8GB unified) · 8 GB

Weights at 1.5 / 8 GBest
Spare memory3.1 GB spare
Usable context33Kwhat the spare memory holds; no published limit on record

Room to spare. 3.1 GB spare means a 10% error in the size would not change the answer.

These cards answer whether Granite 4.0 1b Speech loads, not how fast it transcribes. Throughput figures for a transcription model come from its text decoder, so treat this as a fit answer rather than a speed one.

Your hardware
Checking your profile…

Memory use by level

Against a 24 GB card.

What is quantisation? →
1.5 GBest
Fits in memory
1.7 GBest
Fits in memory
2.5 GBest
Fits in memory
This model on every device we track71 devicesThe Q4 build most people download, on each device: what the weights come to, how much context the memory leaves, and whether it runs. Smallest device that runs it first. This is a fit answer: whether it loads, not how fast it transcribes.
Android phone · 6 GB3 GB1.5 GBest2KFits in memoryest
iPhone 143.3 GB1.5 GBest4KFits in memory
iPhone 153.3 GB1.5 GBest4KFits in memory
Android phone · 8 GB · 2023 or newer4 GB1.5 GBest8KFits in memory
Android phone · 8 GB · 2020–20224 GB1.5 GBest8KFits in memory
iPhone 16 Pro4.4 GB1.5 GBest16KFits in memory
iPhone 174.4 GB1.5 GBest16KFits in memory
iPhone 15 Pro4.4 GB1.5 GBest16KFits in memory
iPhone 164.4 GB1.5 GBest16KFits in memory
GeForce GTX 1660 SUPER6 GB1.5 GBest33KFits in memory
Android phone · 12 GB · 2023 or newer6 GB1.5 GBest33KFits in memory
iPhone 17 Pro6.6 GB1.5 GBest33KFits in memory
GeForce RTX 3060 8GB8 GB1.5 GBest33KFits in memory
GeForce RTX 4060 8GB8 GB1.5 GBest33KFits in memory
Radeon RX 66008 GB1.5 GBest33KFits in memory
Apple M2 (8-core GPU, 8GB unified)8 GB1.5 GBest33KFits in memory
Apple M1 (8-core GPU, 8GB unified)8 GB1.5 GBest33KFits in memory
Android phone · 16 GB · 2024 or newer8 GB1.5 GBest33KFits in memory
Arc B57010 GB1.5 GBest66KFits in memory
GeForce RTX 3080 10GB10 GB1.5 GBest66KFits in memory
Arc B58012 GB1.5 GBest66KFits in memory
GeForce RTX 3060 12GB12 GB1.5 GBest66KFits in memory
GeForce RTX 4070 SUPER12 GB1.5 GBest66KFits in memory
GeForce RTX 507012 GB1.5 GBest66KFits in memory
GeForce RTX 4060 Ti 16GB16 GB1.5 GBest131KFits in memory
GeForce RTX 4070 Ti SUPER16 GB1.5 GBest131KFits in memory
GeForce RTX 4080 SUPER16 GB1.5 GBest131KFits in memory
GeForce RTX 5060 Ti 16GB16 GB1.5 GBest131KFits in memory
GeForce RTX 5070 Ti16 GB1.5 GBest131KFits in memory
GeForce RTX 508016 GB1.5 GBest131KFits in memory
Radeon RX 907016 GB1.5 GBest131KFits in memory
Radeon RX 9070 XT16 GB1.5 GBest131KFits in memory
Apple M1 (8-core GPU)16 GB1.5 GBest66KFits in memory
Radeon RX 7900 XT20 GB1.5 GBest131KFits in memory
GeForce RTX 309024 GB1.5 GBest131KFits in memory
GeForce RTX 3090 Ti24 GB1.5 GBest131KFits in memory
GeForce RTX 409024 GB1.5 GBest131KFits in memory
Radeon RX 7900 XTX24 GB1.5 GBest131KFits in memory
Apple M2 (10-core GPU)24 GB1.5 GBest131KFits in memory
Apple M3 (10-core GPU)24 GB1.5 GBest131KFits in memory
GeForce RTX 509032 GB1.5 GBest262KFits in memory
Apple M1 Pro (16-core GPU)32 GB1.5 GBest131KFits in memory
Apple M2 Pro (19-core GPU)32 GB1.5 GBest131KFits in memory
Apple M5 (10-core GPU)32 GB1.5 GBest131KFits in memory
Apple M4 (10-core GPU)32 GB1.5 GBest131KFits in memory
Apple M3 Pro (18-core GPU)36 GB1.5 GBest262KFits in memory
L40S48 GB1.5 GBest262KFits in memory
RTX 6000 Ada48 GB1.5 GBest262KFits in memory
Apple M1 Max (32-core GPU)64 GB1.5 GBest262KFits in memory
Apple M4 Max (32-core GPU)64 GB1.5 GBest262KFits in memory
Apple M4 Pro (20-core GPU)64 GB1.5 GBest262KFits in memory
Apple M5 Max (32-core GPU)64 GB1.5 GBest262KFits in memory
Apple M5 Pro (20-core GPU)64 GB1.5 GBest262KFits in memory
A100 80GB SXM80 GB1.5 GBest262KFits in memory
H100 80GB SXM80 GB1.5 GBest262KFits in memory
Apple M2 Max (38-core GPU)96 GB1.5 GBest262KFits in memory
RTX PRO 6000 Blackwell96 GB1.5 GBest262KFits in memory
Apple M1 Ultra (64-core GPU)128 GB1.5 GBest262KFits in memory
Apple M3 Max (40-core GPU)128 GB1.5 GBest262KFits in memory
Apple M4 Max (40-core GPU)128 GB1.5 GBest262KFits in memory
Apple M5 Max (40-core GPU)128 GB1.5 GBest262KFits in memory
NVIDIA DGX Spark (GB10)128 GB1.5 GBest262KFits in memory
Ryzen AI Max+ 395 (Radeon 8060S)128 GB1.5 GBest262KFits in memory
H200 141GB SXM141 GB1.5 GBest262KFits in memory
Apple M2 Ultra (76-core GPU)192 GB1.5 GBest262KFits in memory
B200 (SXM 192GB)192 GB1.5 GBest262KFits in memory
Instinct MI300X192 GB1.5 GBest262KFits in memory
Apple M3 Ultra (80-core GPU)512 GB1.5 GBest262KFits in memory
iPhone 132.2 GB1.5 GBestnot calculatedToo large
iPhone SE (3rd gen)2.2 GB1.5 GBestnot calculatedToo large
Android phone · 4 GB2 GB1.5 GBestnot calculatedToo large

Check against your own machine →

02

Models people weigh against Granite 4.0 1b Speech

03

When we formed this view

Recent changes

Sep 11, 2026BenchmarkScored 666.2 on Open ASR RTFx
What movedleaderboard
Sep 11, 2026BenchmarkScored 5.1 on Open ASR WER
What movedleaderboard
Sep 11, 2026BenchmarkScored 8.53 on Accented speech
What movedleaderboard
Sep 11, 2026BenchmarkScored 7.38 on Recorded meetings
What movedleaderboard
Sep 11, 2026BenchmarkScored 1.11 on Clean read speech
What movedleaderboard
Sep 11, 2026BenchmarkScored 2.5 on Harder read speech
What movedleaderboard
Aug 2, 2026BenchmarkScored 3.55 on Financial calls
What movedleaderboard
Aug 2, 2026BenchmarkScored 4.41 on European-accented speech
What movedleaderboard
Aug 2, 2026BenchmarkScored 8.44 on Podcasts and video
What movedleaderboard
Aug 1, 2026ListedListed on LLMap
What movedfirst indexed by our pipeline

Each date is the day we first saw the change, or the day the maker announced it.

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.
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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

Open, few conditionsCommercial use allowed

Fully permissive: commercial use, redistribution, and derivatives allowed. Requires attribution and a copy of the license. Includes an express patent grant.

Identifiers

Architecture
Dense
Takes in, gives back
Audio in, text out
Catalogue slug
ibm-granite-granite-4-0-1b-speech

Machine-readable model card (omc.json) →

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