Fact · Speech recognition
1630times faster than real time
In the paper's Open ASR Leaderboard speed measurements on a single H100 GPU at batch size 96, NLE++ ran at an RTFx of 1630, meaning 1630 times faster than real time.
Quote found word for word on the live source, last checked October 19, 2026
In the source's own words
“NLE++ achieves 5.67% average WER with an RTFx of 1630. ... on a single H100 GPU with bf16 precision”
NLE: Non-autoregressive LLM-based ASR by Transcript Editing, Avihu Dekel et al., arXiv, 2026, Abstract; Section 5.1, Table 2.
Open the original (DOI 10.48550/arXiv.2603.08397)- What it measures
- The paper states that all RTFx measurements use offline batched inference on a single H100 GPU with bf16 precision. RTFx is the audio duration divided by the processing time, so higher is faster.
- What it does not show
- A preprint from one lab's own measurements. The speed depends on batch size, so the batch size is part of each label, and batch 1 is the single-utterance case the paper emphasizes.
In the data
A row of Speech Recognition Speed: Real-Time Factor Data, as Dekel et al. 2026, NLE++ batch 96: 1,630 times faster than real time.
- System
- NLE++ (batch 96)
- Kind
- Research system
- Hardware
- NVIDIA H100 GPU
- Test set
- Open ASR Leaderboard (English average)
- Year
- 2026