Nvidia Nemotron 3.5 Transcribe: open ASR for 40 languages
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Otherwise the answer is really mechanical. It's will run as fast as you can get the weights into your cou's ALUs. since it's 30b-a4b, if you have 30G spare ram you can load the whole thing and it will run about as "fast" as any 4b model (qwen3.5-4b, gemma4 e4b etc).
Otherwise you will be streaming from disk/SSD which may or may not be very slow.
It seems to want an NVidia GPU. I didn't look closely to find out if it can run usably without one. For me, usable might mean 10% of realtime, i.e. an overnight run on my old x86 box for 1 hour of transcription. Of course faster is always nice. YMMV.
If you want an implementation optimized for a certain architecture the cost is between 10-30USD of opus tokens and is oneshottable: ("implement Nvidia nemotron 3.5 transcribe for the intel npu on this machine. Use the hf transformers implementation as reference. The finished artifact takes pcm on stdin and utf8 chunks on stdout".)
You can substitute your old intel CPU by modifying the prompt by replacing "intel npu" with "the target cou on this machine ... Your task is complete when the model decode performance is 80% of the memory read speed of this machine"
Bit unfortunate! Nemotron Streaming in Handy has basically solved dictation for me. It recognizes German mixed with English terms and brand names really well.
Select nemotron in the model selection
Also, there's no mention of Nemotron in that handy. Is that the same Handy GGP was talking about?
I’m still sad Voxtral 3 wasn’t made open source by Mistral.
e: also i'm testing it with a Q4 quant that might not be full accuracy
I was thinking of creating a local app that calls OpenAI’s VTT model. In my most recent evaluation, the OpenAI model was best for my use case. But is that indeed the case?