🧠

Model

LeViT

Name: LeViT
Author: qualcomm

by qualcomm hf-model--qualcomm--levit

Nexus Index

39.9 Top 4%

S: Semantic 50

A: Authority 0

P: Popularity 16

R: Recency 99

Q: Quality 50

Tech Context

Vital Performance

296 DL / 30D

0.0%

Source →

Audited 39.9 FNI Score

Tiny - Params

- Context

Hot 296 Downloads

Restricted OTHER License

Model Information Summary
Entity Passport
Registry ID	hf-model--qualcomm--levit
License	Other
Provider	huggingface

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__qualcomm__levit,
  author = {qualcomm},
  title = {LeViT Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/qualcomm/levit}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

qualcomm. (2026). LeViT [Model]. Free2AITools. https://huggingface.co/qualcomm/levit

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download

huggingface-cli download qualcomm/levit

⚖️ Nexus Index V2.0

Methodology Index Protocol

39.9

TOP 4% SYSTEM IMPACT

Semantic (S) 50

Authority (A) 0

Popularity (P) 16

Recency (R) 99

Quality (Q) 50

💬 Index Insight

FNI V2.0 for LeViT: Semantic (S:50), Authority (A:0), Popularity (P:16), Recency (R:99), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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🚀 What's Next?

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⚡

Technical Deep Dive

LeViT: Optimized for Qualcomm Devices

LeViT is a vision transformer model that can classify images from the Imagenet dataset.

This is based on the implementation of LeViT found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime	Precision	Chipset	SDK Versions	Download
ONNX	float	Universal	QAIRT 2.42, ONNX Runtime 1.24.1	Download
ONNX	w8a16	Universal	QAIRT 2.42, ONNX Runtime 1.24.1	Download
ONNX	w8a16_mixed_int16	Universal	QAIRT 2.42, ONNX Runtime 1.24.1	Download
QNN_DLC	float	Universal	QAIRT 2.43	Download
QNN_DLC	w8a16	Universal	QAIRT 2.43	Download
QNN_DLC	w8a16_mixed_int16	Universal	QAIRT 2.43	Download
TFLITE	float	Universal	QAIRT 2.43, TFLite 2.17.0	Download

For more device-specific assets and performance metrics, visit LeViT on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:

Custom weights (e.g., fine-tuned checkpoints)
Custom input shapes
Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for LeViT on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.image_classification

Model Stats:

Model checkpoint: LeViT-128S
Input resolution: 224x224
Number of parameters: 7.82M
Model size (float): 29.9 MB
Model size (w8a16): 8.83 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
LeViT	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	0.655 ms	1 - 77 MB	NPU
LeViT	ONNX	float	Snapdragon® X2 Elite	0.692 ms	16 - 16 MB	NPU
LeViT	ONNX	float	Snapdragon® X Elite	1.464 ms	16 - 16 MB	NPU
LeViT	ONNX	float	Snapdragon® 8 Gen 3 Mobile	0.861 ms	0 - 93 MB	NPU
LeViT	ONNX	float	Qualcomm® QCS8550 (Proxy)	1.252 ms	0 - 25 MB	NPU
LeViT	ONNX	float	Qualcomm® QCS9075	1.656 ms	1 - 3 MB	NPU
LeViT	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	0.707 ms	0 - 67 MB	NPU
LeViT	ONNX	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	0.469 ms	0 - 62 MB	NPU
LeViT	ONNX	w8a16	Snapdragon® X2 Elite	0.5 ms	8 - 8 MB	NPU
LeViT	ONNX	w8a16	Snapdragon® X Elite	1.239 ms	8 - 8 MB	NPU
LeViT	ONNX	w8a16	Snapdragon® 8 Gen 3 Mobile	0.713 ms	0 - 88 MB	NPU
LeViT	ONNX	w8a16	Qualcomm® QCS6490	46.135 ms	11 - 16 MB	CPU
LeViT	ONNX	w8a16	Qualcomm® QCS8550 (Proxy)	1.039 ms	0 - 13 MB	NPU
LeViT	ONNX	w8a16	Qualcomm® QCS9075	1.262 ms	0 - 3 MB	NPU
LeViT	ONNX	w8a16	Qualcomm® QCM6690	18.543 ms	2 - 12 MB	CPU
LeViT	ONNX	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	0.538 ms	0 - 60 MB	NPU
LeViT	ONNX	w8a16	Snapdragon® 7 Gen 4 Mobile	14.66 ms	11 - 20 MB	CPU
LeViT	ONNX	w8a16_mixed_int16	Snapdragon® 8 Elite Gen 5 Mobile	0.485 ms	0 - 61 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Snapdragon® X2 Elite	0.509 ms	10 - 10 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Snapdragon® X Elite	1.277 ms	10 - 10 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Snapdragon® 8 Gen 3 Mobile	0.737 ms	0 - 84 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Qualcomm® QCS6490	44.528 ms	11 - 17 MB	CPU
LeViT	ONNX	w8a16_mixed_int16	Qualcomm® QCS8550 (Proxy)	1.063 ms	0 - 13 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Qualcomm® QCS9075	1.311 ms	0 - 3 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Qualcomm® QCM6690	18.63 ms	25 - 35 MB	CPU
LeViT	ONNX	w8a16_mixed_int16	Snapdragon® 8 Elite For Galaxy Mobile	0.546 ms	0 - 59 MB	NPU
LeViT	ONNX	w8a16_mixed_int16	Snapdragon® 7 Gen 4 Mobile	15.893 ms	11 - 22 MB	CPU
LeViT	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	0.743 ms	1 - 61 MB	NPU
LeViT	QNN_DLC	float	Snapdragon® X2 Elite	0.999 ms	1 - 1 MB	NPU
LeViT	QNN_DLC	float	Snapdragon® X Elite	1.802 ms	1 - 1 MB	NPU
LeViT	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	1.082 ms	1 - 88 MB	NPU
LeViT	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	3.843 ms	1 - 58 MB	NPU
LeViT	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	1.593 ms	1 - 47 MB	NPU
LeViT	QNN_DLC	float	Qualcomm® QCS9075	1.884 ms	1 - 3 MB	NPU
LeViT	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	2.363 ms	0 - 81 MB	NPU
LeViT	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	0.849 ms	1 - 59 MB	NPU
LeViT	QNN_DLC	w8a16	Snapdragon® 8 Elite Gen 5 Mobile	0.633 ms	0 - 41 MB	NPU
LeViT	QNN_DLC	w8a16	Snapdragon® X2 Elite	0.851 ms	0 - 0 MB	NPU
LeViT	QNN_DLC	w8a16	Snapdragon® X Elite	1.669 ms	0 - 0 MB	NPU
LeViT	QNN_DLC	w8a16	Snapdragon® 8 Gen 3 Mobile	1.017 ms	0 - 61 MB	NPU
LeViT	QNN_DLC	w8a16	Qualcomm® QCS8275 (Proxy)	2.967 ms	0 - 40 MB	NPU
LeViT	QNN_DLC	w8a16	Qualcomm® QCS8550 (Proxy)	1.46 ms	0 - 3 MB	NPU
LeViT	QNN_DLC	w8a16	Qualcomm® QCS9075	1.724 ms	2 - 4 MB	NPU
LeViT	QNN_DLC	w8a16	Qualcomm® QCM6690	5.673 ms	0 - 164 MB	NPU
LeViT	QNN_DLC	w8a16	Snapdragon® 8 Elite For Galaxy Mobile	0.748 ms	0 - 42 MB	NPU
LeViT	QNN_DLC	w8a16	Snapdragon® 7 Gen 4 Mobile	1.473 ms	0 - 39 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Snapdragon® 8 Elite Gen 5 Mobile	0.652 ms	0 - 41 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Snapdragon® X2 Elite	0.858 ms	0 - 0 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Snapdragon® X Elite	1.703 ms	0 - 0 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Snapdragon® 8 Gen 3 Mobile	1.037 ms	0 - 66 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Qualcomm® QCS8275 (Proxy)	3.052 ms	0 - 40 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Qualcomm® QCS8550 (Proxy)	1.493 ms	0 - 12 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Qualcomm® QCS9075	1.745 ms	2 - 4 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Qualcomm® QCM6690	6.08 ms	0 - 166 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Snapdragon® 8 Elite For Galaxy Mobile	0.752 ms	0 - 37 MB	NPU
LeViT	QNN_DLC	w8a16_mixed_int16	Snapdragon® 7 Gen 4 Mobile	1.506 ms	0 - 39 MB	NPU
LeViT	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	0.68 ms	0 - 72 MB	NPU
LeViT	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	1.051 ms	0 - 90 MB	NPU
LeViT	TFLITE	float	Qualcomm® QCS8275 (Proxy)	4.099 ms	0 - 65 MB	NPU
LeViT	TFLITE	float	Qualcomm® QCS8550 (Proxy)	1.56 ms	0 - 2 MB	NPU
LeViT	TFLITE	float	Qualcomm® QCS9075	1.88 ms	0 - 19 MB	NPU
LeViT	TFLITE	float	Qualcomm® QCS8450 (Proxy)	2.399 ms	0 - 83 MB	NPU
LeViT	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	0.802 ms	0 - 72 MB	NPU

License

The license for the original implementation of LeViT can be found here.

References

Community

Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
For questions or feedback please reach out to us.

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.
⚠ License Unknown: Verify licensing terms before commercial use.

Top Tier

Social Proof

HuggingFace Hub

296Downloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--qualcomm--levit
slug: qualcomm--levit
source: huggingface
author: qualcomm
license: Other
tags: pytorch, bu_auto, android, image-classification, arxiv:2104.01136, license:other, region:us

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag: image-classification

📊 Engagement & Metrics

downloads: 296
stars: 0
forks: 0

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