Paraformer (FunASR)
Non-autoregressive ASR model by Alibaba achieving fast parallel transcription.
About
Paraformer is the flagship speech recognition model in FunASR, an industrial speech toolkit from Alibaba's DAMO Academy released under the MIT license, with model weights carrying their own licenses. Unlike autoregressive recognizers that decode token by token, Paraformer predicts an entire utterance in parallel, which yields fast inference at competitive accuracy; the repository reports Chinese character error rates around 8 to 10 percent at well over 100x realtime on GPU. FunASR wraps the model in a complete pipeline: FSMN-VAD segments audio, CT-PUNC restores punctuation, CAM++ handles speaker diarization, and a WebSocket service supports streaming recognition with partial results. The toolkit spans offline, streaming, and edge deployment, including GGUF builds that run without a Python runtime, and newer models in the family extend coverage to dozens of languages. It is used in production speech systems, particularly Chinese transcription workloads where throughput and accuracy both matter.
Should you use Paraformer (FunASR)?
Pick it when
Pick Paraformer when you transcribe large volumes of Chinese and want parallel, non-autoregressive decoding at well over 100x realtime on GPU, with timestamps, VAD, punctuation, and streaming available around it.
Look elsewhere when
Skip it for English-heavy or broadly multilingual audio, since Paraformer centers on Chinese and Whisper-based tools cover far more languages, or when Mandarin accuracy matters more than speed; FireRedASR targets lower error rates.
Alternatives to Paraformer (FunASR)
- FireRedASR
Aims for top Mandarin accuracy and handles dialects and lyrics, but with heavier models and a manual setup compared with Paraformer's speed.
- SenseVoice
Same family and also non-autoregressive, adding Cantonese, Japanese, Korean, emotion, and event tags in a CPU-friendly model.
- Qwen3-ASR
Apache 2.0 with 22 Chinese dialects and 30 languages, where Paraformer centers on Chinese and English with separately licensed weights.
- WeNet
Unifies streaming and batch in one Conformer model with libtorch and TensorRT runtimes, better if you train your own Chinese models.
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Details
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Intermediate (3/5)
- License
- MIT
- Minimum VRAM
- 4 GB
- Added
- Apr 3, 2026