CLIP ViT-B/32 INT8

Edge LinuxRaspberry Pi 5

A quantized vision-language model for zero-shot image classification, pairing an INT8 vision encoder with an FP32 text encoder to produce aligned image and text embeddings for prompt-based similarity scoring and multimodal retrieval-style workflows.View on Hugging Face

Accuracyvs base model

Top-161.56%↑0.83 pp

Top-585.43%↑0.18 pp

Latency

95.5

About this version

Original Model:: clip-vit-base-patch32 by OpenAI — Repository
Optimization/conversion:: Arm-Optimized version for execution on Arm-based platforms.
Converted/optimized by:: Arm
License:: The Original Model and the Optimized Model are subject to MIT.

This repository contains a converted or optimized version of the Original Model (the “Optimized Model”). The Original Model has been converted or optimized as described above for execution on Arm-based platforms.

No retraining or fine-tuning of the Original Model was performed as part of the conversion or optimization. The conversion or optimization was not intended to change the Original Model’s behavior or intended use.

Original Model and Documentation

For information about the Original Model, including its development, training data, intended uses, limitations and other relevant information, please refer to the Original Model repository. Information in that repository was provided by the original developer or other third parties and, unless expressly stated otherwise, has not been independently verified by Arm.

Licenses and Third-Party Terms

Use of the Original Model and the Optimized Model is subject to the applicable licenses, usage restrictions and other terms identified above and in the relevant repositories. Publication of the Optimized Model does not grant any rights beyond those provided under the applicable license terms.

You are responsible for reviewing those terms and ensuring that your use of the Original Model and the Optimized Model is permitted.

Metric	Resultsvs baseline	Change
End to end latency p50	95.50ms298.20ms	−202.70 ms
End to end latency p90	95.66ms298.36ms	−202.69 ms
End to end latency p99	96.36ms298.55ms	−202.19 ms
Peak memory	200.94MB484.20MB	−283.26 MB
Average memory	200.89MB484.16MB	−283.27 MB
Frames per second	10.47fps-fps
Accuracy - Top 1	61.56%60.73%	+0.83%
Accuracy - Top 5	85.43%85.25%	+0.18%

Dataset	cifar100	cifar100
Sample count	10,000	10,000
Batch size	1	1
Input resolution	224x224	224x224
Runs	100	100
Warmup runs	10	10

CLIP ViT-B/32 INT8

CLIP ViT-B/32 INT8

Get Started with this Model

Run optimized image classification models from the Arm AI Portal on Arm-powered Android devices

Deploy an MCP Server on Raspberry Pi 5 for AI agent interaction using OpenAI SDK

Model Evaluation

Configuration

Comparability

Purpose of this Release