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zai-org / GLM-ASR-Nano-2512
Model's Last Updated: April 07 2026
automatic-speech-recognition
Introduction of GLM-ASR-Nano-2512
Model Details of GLM-ASR-Nano-2512
GLM-ASR-Nano-2512
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Model Introduction
GLM-ASR-Nano-2512 is a robust, open-source speech recognition model with 1.5B parameters . Designed for real-world complexity, it outperforms OpenAI Whisper V3 on multiple benchmarks while maintaining a compact size.
Key capabilities include:
-
Exceptional Dialect Support: Beyond standard Mandarin and English, the model is highly optimized for Cantonese (粤语) and other dialects, effectively bridging the gap in dialectal speech recognition.
-
Low-Volume Speech Robustness: Specifically trained for "Whisper/Quiet Speech" scenarios. It captures and accurately transcribes extremely low-volume audio that traditional models often miss.
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SOTA Performance: Achieves the lowest average error rate (4.10) among comparable open-source models, showing significant advantages in Chinese benchmarks (Wenet Meeting, Aishell-1, etc..).
Benchmark
We evaluated GLM-ASR-Nano against leading open-source and closed-source models. The results demonstrate that * GLM-ASR-Nano (1.5B) * achieves superior performance, particularly in challenging acoustic environments.
Notes:
- Wenet Meeting reflects real-world meeting scenarios with noise and overlapping speech.
- Aishell-1 is a standard Mandarin benchmark.
Inference
GLM-ASR-Nano-2512
can be easily integrated using the
transformers
library.
We will support
transformers 5.x
as well as inference frameworks such as
vLLM
and
SGLang
.
you can check more code in
Github
.
Runs of zai-org GLM-ASR-Nano-2512 on huggingface.co
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More Information About GLM-ASR-Nano-2512 huggingface.co Model
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