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	6.17 GB	Likely overkill.
GGML	F16	3.1 GB	Performs better than Q8_0 for noisy audio and music.
GGML	Q8_0	1.66 GB	Sweet spot; superficial quality loss at nearly double the speed.
GGML	Q6_K	1.28 GB
GGML	Q5_K	1.08 GB
GGML	Q5_1	1.18 GB
GGML	Q5_0	1.08 GB	Last "good" quant; anything below loses quality rapidly.
GGML	Q4_K	889 MB	Might not have lost too much quality, but I'm not sure.
GGML	Q4_1	985 MB
GGML	Q4_0	889 MB
GGML	Q3_K	686 MB
GGML	Q2_K	530 MB	Completely non-sensical outputs.

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 v1.8.4 on Windows x64, leveraging CUDA 12.4.0. For the F16 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.

Pomni/whisper-large-v3-russian-ggml-allquants

Whisper-Large-v3-Russian quants