Breeze-ASR-26 β ONNX (sherpa-onnx, INT8)
The only build that runs on Android, iOS, and in the browser (WASM). Encoder and decoder are single ONNX files each. Slower on CPU (RTF 1.3) than CT2/GGML β use this only where you need mobile or WASM; otherwise prefer CT2 (speed) or GGML (low RAM).
Part of the Breeze-ASR-26 edge family β the same MediaTek model in every runtime, pick by your constraint:
Repo Runtime RSS RTF (CPU 4-thread) Best for Breeze-ASR-26-ct2 CTranslate2 / faster-whisper ~2.9 GB 0.21 servers, 8 GB+ hosts, GPU Breeze-ASR-26-GGML whisper.cpp / MacWhisper 1.85 GB 0.40 4 GB hosts, desktop apps Breeze-ASR-26-ONNX sherpa-onnx / onnxruntime β 1.3 Android / iOS / WASM All Apache-2.0, derived from MediaTek-Research/Breeze-ASR-26. Measured on real multi-speaker Mandarin meeting audio. Mandarin does not regress; Taigi is transcribed as Mandarin meaning (not verbatim Taigi characters).
Usage
import sherpa_onnx
rec = sherpa_onnx.OfflineRecognizer.from_whisper(
encoder="breeze-asr-26-large-v2-encoder.int8.onnx",
decoder="breeze-asr-26-large-v2-decoder.int8.onnx",
tokens="breeze-asr-26-large-v2-tokens.txt",
language="zh", task="transcribe", num_threads=4)
Model tree for weemed/Breeze-ASR-26-ONNX
Base model
openai/whisper-large-v2 Finetuned
MediaTek-Research/Breeze-ASR-26