Whisper-Large-v3-Turbo-ONNX

Whisper Large v3 Turbo - ONNX

Official OpenAI Whisper large-v3-turbo checkpoint exported as ONNX encoder/decoder graphs for speech-core and sherpa-onnx-compatible runtimes.

Part of the soniqo.audio speech toolkit. This is the ONNX Runtime bundle used by speech-core for server, desktop, and Android-style runtimes; the graphs remain sherpa-onnx compatible. Browse ONNX bundles in the soniqo ONNX collection.

Model

The FP16 graphs use external *.onnx.data files. Large-style bundles also use external FP32 *.weights files. Keep external-data files beside their matching .onnx files.

Files

Usage

Use with speech-core's native ONNX Whisper runtime:

#include <speech_core/models/onnx_whisper_stt.h>

speech_core::OnnxWhisperStt stt(
    "turbo-encoder.int8.onnx",
    "turbo-decoder.int8.onnx",
    "turbo-tokens.txt");

auto result = stt.transcribe(audio, length, 16000);

The same encoder/decoder/token files can also be loaded by sherpa-onnx:

import sherpa_onnx

recognizer = sherpa_onnx.OfflineRecognizer.from_whisper(
    encoder="turbo-encoder.fp16.onnx",
    decoder="turbo-decoder.fp16.onnx",
    tokens="turbo-tokens.txt",
    language="en",
    task="transcribe",
    provider="cpu",
)

Full FLEURS WER / RTF

M5 Pro, local FLEURS test split, sherpa-onnx CPU provider, language hint supplied, temperature fallback disabled.

Note: the French split contains one 33.54 s clip; sherpa-onnx Whisper processes the first 30 s.

Links

• Website: soniqo.audio
• Speech Core: github.com/soniqo/speech-core
• Docs: soniqo.audio/speech-core
• Blog: soniqo.audio/blog