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▲Voxtral – Frontier open source speech understanding modelsmistral.ai
123 points by meetpateltech 1 days ago | 23 comments
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homarp 22 hours ago [-]
Running Voxtral-Mini-3B-2507 on GPU requires ~9.5 GB of GPU RAM in bf16 or fp16.

Running Voxtral-Small-24B-2507 on GPU requires ~55 GB of GPU RAM in bf16 or fp16.

kamranjon 14 hours ago [-]
Im pretty excited to play around with this. I’ve worked with whisper quite a bit, it’s awesome to have another model in the same class and from Mistral, who tend to be very open. I’m sure unsloth is already working on some GGUF quants - will probably spin it up tomorrow and try it on some audio.
ipsum2 19 hours ago [-]
24B is crazy expensive for speech transcription. Conspicuously no comparison with Parakeet, a 600M param model thats currently dominating leaderboards (but only for English)
azinman2 12 hours ago [-]
But it also includes world knowledge, can do tool calls, etc. It’s an omnimodel
sheerun 15 hours ago [-]
In demo they mention polish prononcuation is pretty bad, spoken as if second language of english-native speaker. I wonder if it's the same for other languages. On the other hand whispering-english is hillariously good, especially different emotions.
Raed667 12 hours ago [-]
It is insane how good the "French man speaking English" demo is. It captures a lot of subtleties
GaggiX 24 hours ago [-]
There is also a Voxtral Small 24B small model available to be downloaded: https://huggingface.co/mistralai/Voxtral-Small-24B-2507
lostmsu 22 hours ago [-]
Does it support realtime transcription? What is the ~latency?
rolisz 7 hours ago [-]
Unlikely. The small model is much larger than whisper (which is already hard to use for realtime)
homarp 1 days ago [-]
weights:https://huggingface.co/mistralai/Voxtral-Mini-3B-2507 and https://huggingface.co/mistralai/Voxtral-Small-24B-2507
homarp 1 days ago [-]
Running Voxtral-Mini-3B-2507 on GPU requires ~9.5 GB of GPU RAM in bf16 or fp16.

Running Voxtral-Small-24B-2507 on GPU requires ~55 GB of GPU RAM in bf16 or fp16.

danelski 1 days ago [-]
They claim to undercut competitors of similar quality by half for both models, yet they released both as Apache 2.0 instead of following smaller - open, larger - closed strategy used for their last releases. What's different here?
halJordan 19 hours ago [-]
They didn't release voxtral large so your question doesn't really make sense
danelski 11 hours ago [-]
It's about what their top offering is at the moment, not having Large in name. Mistral Medium 3 is notably not Mistral Large 3, but it was released as API-only.
wmf 19 hours ago [-]
They're working on a bunch of features so maybe those will be closed. I guess they're feeling generous on the base model.
Havoc 19 hours ago [-]
Probably not looking to directly compete in transcription space
lostmsu 22 hours ago [-]
My Whisper v3 Large Turbo is $0.001/min, so their price comparison is not exactly perfect.
ImageXav 22 hours ago [-]
How did you achieve that? I was looking into it and $0.006/min is quoted everywhere.
lostmsu 22 hours ago [-]
Harvesting idle compute. https://borgcloud.org/speech-to-text
4b11b4 14 hours ago [-]
This is your service?
lostmsu 7 hours ago [-]
Yes
BetterWhisper 20 hours ago [-]
Do you support speaker recognition?
lostmsu 19 hours ago [-]
No. I found models doing that unreliable when there are many speakers.