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For the transcription part, we are looking into W2v-BERT 2.0 as well and will make it available in a live-streaming context. That said, Whisper, especially small (<50ms), is not as compute-heavy; right now, most of the compute is consumed by the LLM.

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No, it's not that it's compute-heavy, especially, it's that the model expects to work on 30-second samples. So if you want sub-second latency, you have to do 30 seconds worth of processing more than once a second. It just multiplies the problem up. If you can't offload it to a gpu it's painfully inefficient.

As to why that might matter: my single 4090 is occupied with most of a Mixtral instance, and I don't especially want to take any compute away from that.

For minimum latency you want a recurrent model that works in the time domain. A Mamba-like model could do it.

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