What are the hardware requirements for Phi 2 Quantize Gptq?

Phi 2 Quantize Gptq requires approximately 1.8 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Phi 2 Quantize Gptq and how large is it?

Phi 2 Quantize Gptq is developed by styalai, a model with 2.8b parameters. 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 Quantize Gptq?

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

Phi 2 Quantize Gptq by styalai — VRAM 1.8GB, 2K context

Name: Phi 2 Quantize Gptq
Author: styalai

Phi 2 Quantize Gptq is an open-source language model by styalai. Features: 2.8b LLM, VRAM: 1.8GB, Context: 2K, Quantized, LLM Explorer Score: 0.11.

4-bit Custom code Endpoints compatible Gptq Phi Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/styalai/phi-2_quantize_gptq

Phi 2 Quantize Gptq Parameters and Internals

Model Type

quantized, language model

Additional Notes

The model Phi-2 by Microsoft has been quantized using GPTQ to 4 bits.

LLM Name	Phi 2 Quantize Gptq
Repository 🤗	https://huggingface.co/styalai/phi-2_quantize_gptq
Model Size	2.8b
Required VRAM	1.8 GB
Updated	2026-08-07
Maintainer	styalai
Model Type	phi
Model Files	1.8 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	PhiForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.38.2
Tokenizer Class	CodeGenTokenizer
Vocabulary Size	51200
Torch Data Type	float16

Rank the Phi 2 Quantize Gptq capabilities

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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

Best Alternatives to Phi 2 Quantize Gptq

Best Alternatives	Context / RAM	Downloads	Likes
... 2 Electrical Engineering GPTQ	2K / 1.8 GB	9	7
Phi2 OSST GPTQ	2K / 1.8 GB	9	1
Phi 2 Orange GPTQ	0K / 1.8 GB	17	4
Phi 2 DPO GPTQ	0K / 1.8 GB	37	5
Phi 2 GPTQ	0K / 1.8 GB	65	30
Dolphin 2 6 Phi 2 GPTQ	0K / 1.8 GB	5	2
LMCocktail Phi 2 V1 GPTQ	0K / 1.8 GB	6	1
Bnb DPO 8bit	2K / 3 GB	7	0
Bnb DPO 8bit	2K / 3 GB	7	0
Phi 2 4bit 64rank	2K / 5.6 GB	13	0

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