Model reference · open weights

react-native-executorch-all-MiniLM-L6

Not for GPU servers Embeddings software-mansion Embeddings 1 build Open weights 42k dl/mo

react-native-executorch-all-MiniLM-L6 is an open-weight embedding model from software-mansion. Built for phones (ExecuTorch). It does not run on a GPU server.

  • react-native-executorch-all-MiniLM-L6 is a model repository by software-mansion that hosts the all-MiniLM-L6-v2 sentence-similarity model exported for the React Native ExecuTorch library.
  • The package includes .pte programs for coreml, vulkan, and xnnpack backends with fp16 or fp32 precision, compatible with the ExecuTorch v1.4.1 runtime.
  • The model is released under the apache-2.0 licence.

Summary of the software-mansion/react-native-executorch-all-MiniLM-L6-v2 model card, 2026-10-01

What it is

Released bysoftware-mansion
Released2025-05-07

From the model card

What software-mansion says about react-native-executorch-all-MiniLM-L6

Read the model card

This repository hosts the all-MiniLM-L6-v2 models exported for the React Native ExecuTorch library as ExecuTorch .pte programs, ready to run on device.

Upstream model: all-MiniLM-L6-v2

Variants

PathBackendPrecision
coreml/all_minilm_l6_v2_coreml_fp16.ptecoremlfp16
vulkan/all_minilm_l6_v2_vulkan_fp16.ptevulkanfp16
xnnpack/all_minilm_l6_v2_xnnpack_fp32.ptexnnpackfp32

Repository structure

config.json                                38 B
coreml/all_minilm_l6_v2_coreml_fp16.pte    43.4 MB
coreml/config.json                         929 B
tokenizer.json                             695 kB
tokenizer_config.json                      350 B
vulkan/all_minilm_l6_v2_vulkan_fp16.pte    43.1 MB
vulkan/config.json                         929 B
xnnpack/all_minilm_l6_v2_xnnpack_fp32.pte  86.2 MB
xnnpack/config.json                        931 B

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, which is the basis of search and RAG.

Running it

Where it runs

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

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