kostasang/whisper-large-v3-turbo-onnx-int8

By kostasang · ↓ 0 · ♥ 0 · Updated 2026-02-06

What's in this repo

This page lists the files in kostasang/whisper-large-v3-turbo-onnx-int8, including decoder_model_quantized.onnx, decoder_with_past_model_quantized.onnx, encoder_model_quantized.onnx.

3 ONNX models (.onnx files)
16 files, including 10 .json, 3 .onnx, 1 .md, 1 .txt
Last updated 2026-02-06

ONNX files

File	Size	Download
decoder_model_quantized.onnx	—	Download
decoder_with_past_model_quantized.onnx	—	Download
encoder_model_quantized.onnx	—	Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

whisper-large-v3-turbo-onnx-int8

This is a INT8 Quantized ONNX version of openai/whisper-large-v3-turbo.

Model Details

Base Model: openai/whisper-large-v3-turbo
Format: ONNX (INT8)
Architecture: arm64

Size Comparison

Version	Size
Base ONNX (FP32)	4198.51 MB
FP16 ONNX	2099.54 MB
INT8 Quantized ONNX	1459.58 MB ←
Compression	2.88x

Usage

from optimum.onnxruntime import ORTModelForSpeechSeq2Seq
from transformers import AutoProcessor

model = ORTModelForSpeechSeq2Seq.from_pretrained("kostasang/whisper-large-v3-turbo-onnx-int8")
processor = AutoProcessor.from_pretrained("kostasang/whisper-large-v3-turbo-onnx-int8")

Quantization Details

This model was quantized using dynamic INT8 quantization with ONNX Runtime.

Quantized Operators: MatMul, Attention, Gemm
Target Architecture: arm64

Model info

optimum

optimum onnx whisper speech-recognition int8 quantized base_model:openai/whisper-large-v3-turbo base_model:quantized:openai/whisper-large-v3-turbo region:us

↓ 0 ♥ 0

Created: 2026-02-04

Updated: 2026-02-06

View on Hugging Face

Files (16)

.gitattributes

README.md

added_tokens.json

config.json

decoder_model_quantized.onnx ONNX

decoder_with_past_model_quantized.onnx ONNX

encoder_model_quantized.onnx ONNX

generation_config.json

merges.txt

normalizer.json

ort_config.json

preprocessor_config.json

special_tokens_map.json

tokenizer.json

tokenizer_config.json

vocab.json

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