NVIDIA's Nemotron 3.5 Transcribe cuts speech error rate to 2.8%
As seen on the 24/7 Wall St. homepage on October 28, 2026.
Nvidia cut its own best transcription error rate from 4.3% to 2.8% and now shares the top open-weight spot, a reminder that its moat is software as much as silicon.
Nemotron 3.5 Transcribe's 2.8% WER on the AA-WER Index ties it with Voxtral Small for #1 among open-weight models, ahead of Thinking Machines' Inkling at 3.5%. It improves on NVIDIA's previous most accurate model, Canary Qwen 2.5B, at 4.3%. https://t.co/Hb5R76kipp
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Nemotron 3.5 Transcribe posted a 2.8% word error rate on the AA-WER Index, matching Voxtral Small at the top of the open-weight speech recognition leaderboard and placing Thinking Machines' Inkling third.
The move from NVIDIA's previous best, Canary Qwen 2.5B, to 2.8% is a meaningful compression of errors. That kind of gain matters in production environments where transcription accuracy directly affects downstream tasks like search, compliance recording, and voice interfaces.
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The open-weight classification is important context: these models can be downloaded, fine-tuned, and deployed without API fees, so a top-ranked open-weight model carries real commercial weight for enterprises that want to run inference on their own infrastructure.
NVIDIA's ability to claim the accuracy lead with a software model reinforces the argument that its competitive position extends well beyond chip sales. Investors watching the stock for signs of durable software revenue now have a concrete leaderboard result to point to.
Mentioned: NVDA