Model reference · open weights

react-native-executorch-clip-vit-patch32

Not for GPU servers Embeddings software-mansion Image embed 1 build Open weights 9k dl/mo

react-native-executorch-clip-vit-patch32 is an open-weight embedding model from software-mansion. Built for phones (ExecuTorch) — it does not run on a GPU server.

react-native-executorch-clip-vit-patch32 is a set of exported models for the React Native ExecuTorch library, designed for image feature extraction tasks. The package includes variants for CoreML, MLX, Vulkan, and XNNPACK backends with precision levels ranging from int8 to fp32. It is published under the MIT license and requires the ExecuTorch v1.4.1 runtime.

Summary of the software-mansion/react-native-executorch-clip-vit-base-patch32 model card, 2026-10-01

What it is

Released bysoftware-mansion
TypeEmbedding models
TaskImage embed
Runs withexecutorch
Released2025-07-14
Popularity9k downloads / month
LicenceOpen weights

From the model card

What software-mansion says about react-native-executorch-clip-vit-patch32

Read the model card

This repository hosts the clip-vit-base-patch32 models exported for the React Native ExecuTorch library as ExecuTorch .pte programs, ready to run on device.

Upstream model: clip-vit-base-patch32

Variants

PathComponentBackendPrecision
coreml/clip_vit_base_patch32_image_coreml_fp16.pteimagecoremlfp16
coreml/clip_vit_base_patch32_text_coreml_fp16.ptetextcoremlfp16
mlx/clip_vit_base_patch32_image_mlx_int8.pte-mlxint8
vulkan/clip_vit_base_patch32_image_vulkan_fp16.pteimagevulkanfp16
vulkan/clip_vit_base_patch32_text_vulkan_fp16.ptetextvulkanfp16
xnnpack/clip_vit_base_patch32_image_xnnpack_fp32.pteimagexnnpackfp32
xnnpack/clip_vit_base_patch32_text_xnnpack_fp32.ptetextxnnpackfp32

Repository structure

config.json                                           43 B
coreml/clip_vit_base_patch32_image_coreml_fp16.pte    168 MB
coreml/clip_vit_base_patch32_text_coreml_fp16.pte     122 MB
coreml/config.json                                    1.7 kB
mlx/clip_vit_base_patch32_image_mlx_int8.pte          93.7 MB
mlx/config.json                                       840 B
tokenizer.json                                        2.1 MB
vulkan/clip_vit_base_patch32_image_vulkan_fp16.pte    168 MB
vulkan/clip_vit_base_patch32_text_vulkan_fp16.pte     121 MB
vulkan/config.json                                    1.7 kB
xnnpack/clip_vit_base_patch32_image_xnnpack_fp32.pte  335 MB
xnnpack/clip_vit_base_patch32_text_xnnpack_fp32.pte   242 MB
xnnpack/config.json                                   1.6 kB

Compatibility

These files are published for the ExecuTorch v1.4.1 runtime. ExecuTorch gives no forward compatibility guarantee, so an older runtime may fail to load them.

To use them in React Native ExecuTorch, pass the model constant shipped in the library's model registry to the corresponding task pipeline. See the documentation.

To load these files in your own ExecuTorch runtime, read the compatibility note first.

Quoted from the model card on Hugging Face — the full card is behind the Hugging Face link above.

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Running it

Where it runs

Built for phones (ExecuTorch) — it does not run on a GPU server.

© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms