Magpie-TTS needs a kernel compiled targeting Ampere, but it appears to be closed source. It was compiled for the 2018 T4, but not 2020-2024 consumer cards, just 2025 consumer cards.
I actually forked the repo, modified the Dockerfile and build/run scripts targeting Ampere and the whole setup is running seamlessly on my 3090, Magpie is running fine and using under 3Gb of memory, ~2Gb for nemotron STT, and ~18Gb for Nemotron Nano 30b. Latencies are great and the turn detection works really well!
I'm going to use this setup as the base for a language learning App for my gf :)
Make sure you’re using the nemotron-speech asr model. I added support for Spanish via Canary models but these have like 10x the latency: 160ms on nemotron-speech vs 1.5s canary.
For the LLM I’m currently using Mistral-Small-3.2-24B-Instruct instead of Nemotron 3 and it works well for my use case
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Any ideas on how to add Ampere support? I have a use case in mind that I would love to try on my 3090 rig
Magpie-TTS needs a kernel compiled targeting Ampere, but it appears to be closed source. It was compiled for the 2018 T4, but not 2020-2024 consumer cards, just 2025 consumer cards.
I actually forked the repo, modified the Dockerfile and build/run scripts targeting Ampere and the whole setup is running seamlessly on my 3090, Magpie is running fine and using under 3Gb of memory, ~2Gb for nemotron STT, and ~18Gb for Nemotron Nano 30b. Latencies are great and the turn detection works really well!
I'm going to use this setup as the base for a language learning App for my gf :)
I got your fork working (also on a 3090). I was not impressed with the latency or the recommended LLM’s quality.
Make sure you’re using the nemotron-speech asr model. I added support for Spanish via Canary models but these have like 10x the latency: 160ms on nemotron-speech vs 1.5s canary.
For the LLM I’m currently using Mistral-Small-3.2-24B-Instruct instead of Nemotron 3 and it works well for my use case