# NVIDIA's Nemotron 3.5 Transcribe ties for top open-weights speech-to-text accuracy

> Original title: NVIDIA's Nemotron 3.5 Transcribe ties for #1 among open weights Speech to Text models with 2.8% WER, using just 4B active parameters

- Source: Artificial Analysis
- Published: 2026-10-28T15:05:14.000Z
- Bad Influence: https://badinfluence.news/items/w4vok6xr2l9ci7uau3gwclkyu
- Original: https://x.com/ArtificialAnlys/status/2115459886045942161

## Summary

NVIDIA releases Nemotron 3.5 Transcribe, an open-weights non-streaming speech-to-text model with 30B total and 4B active parameters. It scores 2.8% on Artificial Analysis's AA-WER Index, tying Mistral's Voxtral Small for first among open-weights models, and 1.8% versus 2.3% on AA-AgentTalk, a voice agent conversation dataset. Voxtral Small has 24B active parameters, six times as many as Nemotron 3.5 Transcribe.

## Post

NVIDIA's Nemotron 3.5 Transcribe ties for #1 among open weights Speech to Text models with 2.8% WER, using just 4B active parameters

Nemotron 3.5 Transcribe is NVIDIA's new open weights Speech to Text model for non-streaming transcription, with 30B total and 4B active parameters, and the most accurate NVIDIA model on our non-streaming Speech to Text leaderboard.

Key takeaways

➤ Accuracy: Nemotron 3.5 Transcribe scores 2.8% on the AA-WER Index, tied with Mistral's Voxtral Small for #1 among open-weight models. It leads Voxtral Small on AA-AgentTalk, our dataset of voice agent conversations, at 1.8% vs. 2.3%.

➤ Model size: With 4B active parameters (30B total), Nemotron 3.5 Transcribe sits on the open weights frontier of AA-WER vs. active parameters. It matches the accuracy of Mistral's Voxtral Small with 6x fewer active parameters (4B vs. 24B), while other open weights models of a similar size sit at around 4% WER.

Congratulations to @NVIDIAAI on the release!

See more details below ⬇️

![](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FHVuecCsbgAA39bB.jpg&mode=thumb&exp=1793404800&sig=9a481caaa01f8b36)