What are the hardware requirements for Phi 2 Orange GGUF?

Phi 2 Orange GGUF requires approximately 1.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Phi 2 Orange GGUF and how large is it?

Phi 2 Orange GGUF is developed by TheBloke. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Phi 2 Orange GGUF?

Phi 2 Orange GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Phi 2 Orange GGUF by TheBloke — VRAM 1.1GB

Name: Phi 2 Orange GGUF
Author: TheBloke

Phi 2 Orange GGUF is an open-source language model by TheBloke. Features: LLM, VRAM: 1.1GB, License: mit, Quantized, LLM Explorer Score: 0.11.

Base model:quantized:rhysjones... Base model:rhysjones/phi-2-ora... Dataset:argilla/ultrafeedback-... Dataset:intel/orca dpo pairs Dataset:ldjnr/capybara Dataset:ldjnr/pure-dove Dataset:ldjnr/verified-camel Dataset:meta-math/metamathqa Dataset:migtissera/synthia-v1.... Dataset:open-orca/slimorca-ded... Gguf Phi-msft Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/phi-2-orange-GGUF

Phi 2 Orange GGUF Parameters and Internals

Model Type

phi-msft

Additional Notes

A two-step finetune of Phi-2, with a bit of zest. First using a collection of broad training data, and then a DPO finetune.

Training Details

Data Sources:

Open-Orca/SlimOrca-Dedup, migtissera/Synthia-v1.3, LDJnr/Verified-Camel, LDJnr/Pure-Dove, LDJnr/Capybara, meta-math/MetaMathQA, Intel/orca_dpo_pairs, argilla/ultrafeedback-binarized-preferences-cleaned

LLM Name	Phi 2 Orange GGUF
Repository 🤗	https://huggingface.co/TheBloke/phi-2-orange-GGUF
Model Name	Phi 2 Orange
Model Creator	Rhys Jones
Base Model(s)	Phi 2 Orange rhysjones/phi-2-orange
Required VRAM	1.1 GB
Updated	2026-08-07
Maintainer	TheBloke
Model Type	phi-msft
Model Files	1.1 GB 1.6 GB 1.5 GB 1.2 GB 1.6 GB 1.8 GB 1.6 GB 1.9 GB 2.1 GB 1.9 GB 2.3 GB 3.0 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	mit

Rank the Phi 2 Orange GGUF capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/phi-2-orange-GGUF.