Phi-4-mini-instruct-onnx ONNX download (52 MB) | Hugging Bay

Q: What is this model?

microsoft/Phi-4-mini-instruct-onnx is an open-weights language model for general published by microsoft, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: microsoft/Phi-4-mini-instruct-onnx

Q: Can I use it commercially?

It is released under the mit license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: 20 files, 96.1 MB. The full repository size is not recorded. The recommended download, model.onnx, is 52.1 MB.

Q: What can I download here?

Hosted here: 20 files, 96.1 MB. Full repo upstream: unknown. The original release is at https://huggingface.co/microsoft/Phi-4-mini-instruct-onnx.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 20 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-microsoft-phi-4-mini-instruct-onnx/safety on Hugging Bay.

Q: Will microsoft/Phi-4-mini-instruct-onnx run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

microsoft

Phi-4-mini-instruct-onnx

microsoft/Phi-4-mini-instruct-onnx

Model details

generalLicense: mitSHA-256 recorded for 20 of 27 filesONNX

Content controls: not assessed.

The catalog does not give enough information to describe what this model is for. Catalog sources: license.

View as JSON →

Your next step

Use it from code

This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-microsoft-phi-4-mini-instruct-onnx/cpu_and_mobile%2Fcpu-int4-rtn-block-32-acc-level-4%2Fmodel.onnx",
    "model.onnx",
)

Other ways

This file cannot open in the app. The app supports one GGUF file at a time.

See app requirements

20 hosted of 27 listed · Hashes recorded. Date not recorded.

Selected downloadcpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/model.onnx52 MB · 1 file Download · 52 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

20 hosted of 27 listed

Hashes recorded. Date not recorded.

File	आकार	SHA-256	स्रोत	डाउनलोड करें
Weights
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/model.onnx` Default	52.1 MB	`701aa5d1…812d0b83` `701aa5d185b6a782bc27104a990dd5b634fa507840b7c42f7ee6f1fb812d0b83`	Hosted	डाउनलोड करें
Tokenizer & config
`config.json`	2.5 KB	`ac65d860…5d5b933b` `ac65d86061d3d0d704ee2511fd0eb8713ef19eb6eedba17c3080a4165d5b933b`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/added_tokens.json`	249 bytes	`d4f2aceb…571af486` `d4f2aceb0f20b71dd1f4bcc7e052e4412946bf281840b8f83d39f259571af486`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/config.json`	2.5 KB	`ac65d860…5d5b933b` `ac65d86061d3d0d704ee2511fd0eb8713ef19eb6eedba17c3080a4165d5b933b`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/genai_config.json`	1.52 KB	`0fcfa1e6…19171470` `0fcfa1e663f2bc867f8dc62fae65dd0924f0a4d68b43d1234df742dd19171470`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/merges.txt`	2.42 MB	`856ce611…791fb4ad` `856ce61180bb689282eed6b3a6838bb1f438399be23aefe9d20eb379791fb4ad`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/special_tokens_map.json`	587 bytes	`aff38493…89ac7cc3` `aff38493227d813e29fcf8406e8e90062f1f031aa47d589325e9c31d89ac7cc3`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/tokenizer.json`	15.5 MB	`382cc235…e90e91ea` `382cc235b56c725945e149cc25f191da667c836655efd0857b004320e90e91ea`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/tokenizer_config.json`	2.96 KB	`c565326a…577a7dec` `c565326a315fbe62cda093a59d298828c8f3f823122661325f41f3ba577a7dec`	Hosted	डाउनलोड करें
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/vocab.json`	3.91 MB	`6cb65a85…f39e98bd` `6cb65a857824fa6615bb1782d95d882617a8bbce1da0317118586b36f39e98bd`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/added_tokens.json`	249 bytes	`d4f2aceb…571af486` `d4f2aceb0f20b71dd1f4bcc7e052e4412946bf281840b8f83d39f259571af486`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/config.json`	2.5 KB	`ac65d860…5d5b933b` `ac65d86061d3d0d704ee2511fd0eb8713ef19eb6eedba17c3080a4165d5b933b`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/genai_config.json`	1.57 KB	`3cdbd2ff…d22b1140` `3cdbd2ff0b2cda7829b262cda331a72b99daaa758d55bb056bb4d098d22b1140`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/merges.txt`	2.42 MB	`856ce611…791fb4ad` `856ce61180bb689282eed6b3a6838bb1f438399be23aefe9d20eb379791fb4ad`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/model.onnx`	286.7 KB	`f8ff300b…a8d25250` `f8ff300b85719f79f1c220c88575626c62cc772a228244a6b96031d1a8d25250`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/special_tokens_map.json`	587 bytes	`aff38493…89ac7cc3` `aff38493227d813e29fcf8406e8e90062f1f031aa47d589325e9c31d89ac7cc3`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/tokenizer.json`	15.5 MB	`382cc235…e90e91ea` `382cc235b56c725945e149cc25f191da667c836655efd0857b004320e90e91ea`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/tokenizer_config.json`	2.96 KB	`c565326a…577a7dec` `c565326a315fbe62cda093a59d298828c8f3f823122661325f41f3ba577a7dec`	Hosted	डाउनलोड करें
`gpu/gpu-int4-rtn-block-32/vocab.json`	3.91 MB	`6cb65a85…f39e98bd` `6cb65a857824fa6615bb1782d95d882617a8bbce1da0317118586b36f39e98bd`	Hosted	डाउनलोड करें
`configuration_phi3.py`	0 bytes	—	Upstream only	File metadata
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/configuration_phi3.py`	0 bytes	—	Upstream only	File metadata
`cpu_and_mobile/cpu-int4-rtn-block-32-acc-level-4/model.onnx.data`	0 bytes	—	Upstream only	File metadata
`gpu/gpu-int4-rtn-block-32/configuration_phi3.py`	0 bytes	—	Upstream only	File metadata
`gpu/gpu-int4-rtn-block-32/model.onnx.data`	0 bytes	—	Upstream only	File metadata
Docs
`README.md`	4.66 KB	`a7b2d46a…651342fe` `a7b2d46a8e5bd4c98a06a20dd4ffe9a031294ff9ff366a801189d942651342fe`	Hosted	डाउनलोड करें
`.gitattributes`	0 bytes	—	Upstream only	File metadata
`LICENSE`	0 bytes	—	Upstream only	File metadata

डाउनलोड की जाँच करें

In the folder where you saved model.onnx, run:

macOS

shasum -a 256 -- 'model.onnx'

Linux

sha256sum -- 'model.onnx'

Windows

Get-FileHash -LiteralPath 'model.onnx' -Algorithm SHA256

Compare the result with the recorded SHA-256.

Phi-4-mini-instruct-onnx

डाउनलोड की जाँच करें

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