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whisper-medium-ggml-allquants
Pomni/whisper-medium-ggml-allquants
whisper-medium-ggml-allquants is a automatic speech recognition model from Pomni. Use it when you need speech turned into text. The card lists the license as apache-2.0.
This is a repository of GGML quants for whisper-medium, for use with whisper.cpp.
Access
Public
Updated Feb 7, 2026
Repo size
9.7 GB
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0
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Repo makeup
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.bin9.7 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- License
- apache-2.0
- Access
- Public
- Created
- Aug 25, 2025
- Updated
- Feb 7, 2026
- SHA
- 61e51382
Base models
Model card
From the Hugging Face model README
Whisper-Medium quants
This is a repository of GGML quants for whisper-medium, for use with whisper.cpp.
If you are looking for a program to run this model with, then I would recommend EasyWhisper UI, as it is user-friendly, has a GUI, and will automate a lot of the hard stuff for you.
List of Quants
Clicking on a link will download the corresponding quant instantly.
| Link | Quant | Size | Notes |
|---|---|---|---|
| GGML | F32 | 3.06 GB | Likely overkill. |
| GGML | F16 | 1.53 GB | Performs better than Q8_0 for noisy audio and music. |
| GGML | Q8_0 | 823 MB | Sweet spot; superficial quality loss at nearly double the speed. |
| GGML | Q6_K | 640 MB | |
| GGML | Q5_K | 539 MB | |
| GGML | Q5_1 | 587 MB | |
| GGML | Q5_0 | 539 MB | Last "good" quant; anything below loses quality rapidly. |
| GGML | Q4_K | 445 MB | Might not have lost too much quality, but I'm not sure. |
| GGML | Q4_1 | 492 MB | |
| GGML | Q4_0 | 445 MB | |
| GGML | Q3_K | 344 MB | |
| GGML | Q2_K | 267 MB | Completely non-sensical outputs. |
The F16 quant was taken from ggerganov/whisper.cpp/ggml-medium.bin.
Questions you may have
Why do the "K-quants" not work for me?
My guess is that your GPU might be too old to recognize them, considering that I have gotten the same error on my GTX 1080. If you would like to run them regardless, you can try switching to CPU inference.
Are the K-quants "S", "M", or "L"?
The quantizer I was using was not specific about this, so I do not know about this either.
What program did you use to make these quants?
I used whisper.cpp v1.7.6 on Windows x64, leveraging CUDA 12.4.0. For the F32 quant, I converted the original Hugging Face (H5) format model to a GGML using the models/convert-h5-to-ggml.py script.
One or multiple of the quants are not working for me.
Open a new discussion in the community tab about this, and I will look into the issue.
- Task
- Automatic Speech Recognition
- License
- apache-2.0
- Languages
- en, zh, de, es, ru, ko
- Created
- Aug 25, 2025
- Updated
- Feb 7, 2026