What are the hardware requirements for LMCocktail Phi 2 V1 GGUF?

LMCocktail Phi 2 V1 GGUF requires approximately 1.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed LMCocktail Phi 2 V1 GGUF and how large is it?

LMCocktail Phi 2 V1 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 LMCocktail Phi 2 V1 GGUF?

LMCocktail Phi 2 V1 GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

LMCocktail Phi 2 V1 GGUF by TheBloke — VRAM 1.2GB

Name: LMCocktail Phi 2 V1 GGUF
Author: TheBloke

LMCocktail Phi 2 V1 GGUF is an open-source language model by TheBloke. Features: LLM, VRAM: 1.2GB, Quantized, LLM Explorer Score: 0.1.

Arxiv:2311.13534 Base model:quantized:yhyu13/lm... Base model:yhyu13/lmcocktail-p... Gguf Phi-msft Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/LMCocktail-phi-2-v1-GGUF

LMCocktail Phi 2 V1 GGUF Parameters and Internals

Model Type

phi-msft

LLM Name	LMCocktail Phi 2 V1 GGUF
Repository 🤗	https://huggingface.co/TheBloke/LMCocktail-phi-2-v1-GGUF
Model Name	LMCocktail Phi 2 v1
Model Creator	Yu
Base Model(s)	LMCocktail Phi 2 V1 Yhyu13/LMCocktail-phi-2-v1
Required VRAM	1.2 GB
Updated	2026-08-03
Maintainer	TheBloke
Model Type	phi-msft
Model Files	1.2 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

Rank the LMCocktail Phi 2 V1 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/LMCocktail-phi-2-v1-GGUF.